---
title: v3.0 Feature Tracking
---

This document tracks major features in FastMCP v3.0 for release notes preparation.

## 3.0.0rc1

### SamplingTool Conversion Helpers

Server tools (FunctionTool and TransformedTool) can now be passed directly to sampling methods via `SamplingTool.from_callable_tool()` ([#3062](https://github.com/PrefectHQ/fastmcp/pull/3062)). Previously, tools defined with `@mcp.tool` had to be recreated as functions for use in `ctx.sample()`. Now `ctx.sample()` and `ctx.sample_step()` accept these tool instances directly.

```python
@mcp.tool
def search(query: str) -> str:
    """Search the web."""
    return do_search(query)

# Use tool directly in sampling
result = await ctx.sample(
    "Research Python frameworks",
    tools=[search]  # FunctionTool works directly!
)
```

### Google GenAI Sampling Handler

FastMCP now includes a sampling handler for Google's Gemini models ([#2977](https://github.com/jlowin/fastmcp/pull/2977)). This enables MCP clients to use Google's GenAI models with the sampling protocol, including full tool calling support.

```python
from fastmcp import Client
from fastmcp.client.sampling.handlers.google_genai import GoogleGenaiSamplingHandler
from google.genai import Client as GoogleGenaiClient

# Initialize the handler
handler = GoogleGenaiSamplingHandler(
    default_model="gemini-2.0-flash-exp",
    client=GoogleGenaiClient(),  # Optional - creates one if not provided
)

# Use with MCP sampling (handler is configured at Client construction)
async with Client("http://server/mcp", sampling_handler=handler) as client:
    result = await client.sample(
        messages=[...],
        tools=[...],
    )
```

Key features:
- Converts MCP tool schemas to Google's function calling format
- Supports all Google GenAI models that implement function calling
- Handles nullable types, nested objects, and arrays in tool schemas
- Properly maps tool choices (`auto`, `required`, `none`) to Google's configuration
- Preserves model preferences from MCP sampling parameters

The handler joins the existing Anthropic and OpenAI handlers, providing a consistent interface for model-agnostic sampling across providers.

### Concurrent Tool Execution in Sampling

When an LLM returns multiple tool calls in a single sampling response, they can now be executed concurrently ([#3022](https://github.com/PrefectHQ/fastmcp/pull/3022)). Default behavior remains sequential; opt in with `tool_concurrency`. Tools can declare `sequential=True` to force sequential execution even when concurrency is enabled.

```python
result = await context.sample(
    messages="Fetch weather for NYC and LA",
    tools=[fetch_weather],
    tool_concurrency=0,  # Unlimited parallel execution
)
```

### OpenAPI `validate_output` Option

`OpenAPIProvider` and `FastMCP.from_openapi()` now accept `validate_output=False` to skip output schema validation ([#3134](https://github.com/PrefectHQ/fastmcp/pull/3134)). Useful when backends don't conform to their own OpenAPI response schemas — structured JSON still flows through, only the strict schema checking is disabled.

```python
mcp = FastMCP.from_openapi(
    openapi_spec=spec,
    client=client,
    validate_output=False,
)
```

### Auth Token Injection and Azure OBO Dependencies

New dependency injection for accessing the authenticated user's token directly in tool parameters ([#2918](https://github.com/PrefectHQ/fastmcp/pull/2918)). Works with any auth provider.

```python
from fastmcp.server.dependencies import CurrentAccessToken, TokenClaim
from fastmcp.server.auth import AccessToken

@mcp.tool()
async def my_tool(
    token: AccessToken = CurrentAccessToken,
    user_id: str = TokenClaim("oid"),
): ...
```

For Azure/Entra, the new `fastmcp[azure]` extra adds `EntraOBOToken`, which handles the On-Behalf-Of token exchange declaratively:

```python
from fastmcp.server.auth.providers.azure import EntraOBOToken

@mcp.tool()
async def get_emails(
    graph_token: str = EntraOBOToken(["https://graph.microsoft.com/Mail.Read"]),
):
    # graph_token is ready — OBO exchange happened automatically
    ...
```

### `generate-cli` Agent Skill Generation

`fastmcp generate-cli` now produces a `SKILL.md` alongside the CLI script ([#3115](https://github.com/PrefectHQ/fastmcp/pull/3115)) — a Claude Code agent skill with pre-computed invocation syntax for every tool. Agents reading the skill can call tools immediately without running `--help`. On by default; pass `--no-skill` to opt out.

### Background Task Notification Queue

Background tasks now use a distributed Redis notification queue for reliable delivery ([#2906](https://github.com/PrefectHQ/fastmcp/pull/2906)). Elicitation switches from polling to BLPOP (single blocking call instead of ~7,200 round-trips/hour), and notification delivery retries up to 3x with TTL-based expiration.

### Async Auth Checks

Auth check functions can now be `async`, enabling authorization decisions that depend on asynchronous operations like reading server state via `Context.get_state` or calling external services ([#3150](https://github.com/PrefectHQ/fastmcp/issues/3150)). Sync and async checks can be freely mixed. Previously, passing an async function as an auth check would silently pass (coroutine objects are truthy).

### Optional `$ref` Dereferencing in Schemas

Schema `$ref` dereferencing — which inlines all `$defs` for compatibility with MCP clients that don't handle `$ref` — is now controlled by the `dereference_schemas` constructor kwarg ([#3141](https://github.com/PrefectHQ/fastmcp/issues/3141)). Default is `True` (dereference on) because the non-compliant clients are popular and the failure mode is silent breakage that server authors can't diagnose. Opt out when you know your clients handle `$ref` and want smaller schemas:

```python
mcp = FastMCP("my-server", dereference_schemas=False)
```

Dereferencing is implemented as middleware (`DereferenceRefsMiddleware`) that runs at serve-time, so schemas are stored with `$ref` intact and only inlined when sent to clients.

### Breaking: Deprecated `FastMCP()` Constructor Kwargs Removed

Sixteen deprecated keyword arguments have been removed from `FastMCP.__init__`. Passing any of them now raises `TypeError` with a migration hint. Environment variables (e.g., `FASTMCP_HOST`) continue to work — only the constructor kwargs moved.

**Transport/server settings** (`host`, `port`, `log_level`, `debug`, `sse_path`, `message_path`, `streamable_http_path`, `json_response`, `stateless_http`): Pass to `run()`, `run_http_async()`, or `http_app()` as appropriate, or set via environment variables.

```python
# Before
mcp = FastMCP("server", host="0.0.0.0", port=8080)
mcp.run()

# After
mcp = FastMCP("server")
mcp.run(transport="http", host="0.0.0.0", port=8080)
```

**Duplicate handling** (`on_duplicate_tools`, `on_duplicate_resources`, `on_duplicate_prompts`): Use the unified `on_duplicate=` parameter.

**Tag filtering** (`include_tags`, `exclude_tags`): Use `server.enable(tags=..., only=True)` and `server.disable(tags=...)` after construction.

**Tool serializer** (`tool_serializer`): Return `ToolResult` from tools instead.

**Tool transformations** (`tool_transformations`): Use `server.add_transform(ToolTransform(...))` after construction.

The `_deprecated_settings` attribute and `.settings` property are also removed. `ExperimentalSettings` has been deleted (dead code).

### Breaking: `ui=` Renamed to `app=`

The MCP Apps decorator parameter has been renamed from `ui=ToolUI(...)` / `ui=ResourceUI(...)` to `app=AppConfig(...)` ([#3117](https://github.com/PrefectHQ/fastmcp/pull/3117)). `ToolUI` and `ResourceUI` are consolidated into a single `AppConfig` class. Wire format is unchanged. See the MCP Apps section under beta2 for full details.
## 3.0.0beta2

### CLI: `fastmcp list` and `fastmcp call`

New client-side CLI commands for querying and invoking tools on any MCP server — remote URLs, local Python files, MCPConfig JSON, or arbitrary stdio commands. Especially useful for giving LLMs that don't have built-in MCP support access to MCP tools via shell commands.

```bash
# Discover tools on a server
fastmcp list http://localhost:8000/mcp
fastmcp list server.py
fastmcp list --command 'npx -y @modelcontextprotocol/server-github'

# Call a tool
fastmcp call server.py greet name=World
fastmcp call http://localhost:8000/mcp search query=hello limit=5
fastmcp call server.py create_item '{"name": "Widget", "tags": ["a", "b"]}'
```

Key features:
- Tool arguments are auto-coerced using the tool's JSON schema (`limit=5` → int)
- Single JSON objects work as positional args alongside `key=value` and `--input-json`
- `--input-schema` / `--output-schema` for full JSON schemas, `--json` for machine-readable output
- `--transport sse` for SSE servers, `--command` for stdio servers
- Auto OAuth for HTTP targets (no-ops if server doesn't require auth)
- Fuzzy tool name matching suggests alternatives on typos
- Interactive terminal elicitation for tools that request user input mid-execution

Documentation: [CLI Querying](/cli/client)

### CLI: `fastmcp discover` and name-based resolution

`fastmcp discover` scans editor configs (Claude Desktop, Claude Code, Cursor, Gemini CLI, Goose) and project-level `mcp.json` files for MCP server definitions. Discovered servers can be referenced by name — or `source:name` for precision — in `fastmcp list` and `fastmcp call`.

```bash
# See all configured servers
fastmcp discover

# Use a server by name
fastmcp list weather
fastmcp call weather get_forecast city=London

# Target a specific source with source:name
fastmcp list claude-code:my-server
fastmcp call cursor:weather get_forecast city=London

# Filter discovery to specific sources
fastmcp discover --source claude-code --source cursor
```

Documentation: [CLI Querying](/cli/client)

### CLI: Expanded Reload File Watching

The `--reload` flag now watches a comprehensive set of file types, making it suitable for MCP apps with frontend bundles ([#3028](https://github.com/PrefectHQ/fastmcp/pull/3028)). Previously limited to `.py` files, it now watches JavaScript, TypeScript, HTML, CSS, config files, and media assets.

### CLI: fastmcp install stdio

The new `fastmcp install stdio` command generates full `uv run` commands for running FastMCP servers over stdio ([#3032](https://github.com/PrefectHQ/fastmcp/pull/3032)).

```bash
# Generate command for a server
fastmcp install stdio server.py

# Outputs:
# uv run --directory /path/to/project fastmcp run server.py
```

The command automatically detects the project directory and generates the appropriate `uv run` invocation, making it easy to integrate FastMCP servers with MCP clients.

### CIMD (Client ID Metadata Documents)

CIMD provides an alternative to Dynamic Client Registration for OAuth-authenticated MCP servers. Instead of registering with each server dynamically, clients host a static JSON document at an HTTPS URL. That URL becomes the client's `client_id`, and servers verify identity through domain ownership.

**Client usage:**

```python
from fastmcp import Client
from fastmcp.client.auth import OAuth

async with Client(
    "https://mcp-server.example.com/mcp",
    auth=OAuth(
        client_metadata_url="https://myapp.example.com/oauth/client.json",
    ),
) as client:
    await client.ping()
```

The `OAuth` helper now supports deferred binding — `mcp_url` is optional when using `OAuth` with `Client(auth=...)`, since the transport provides the server URL automatically.

**CLI tools for document management:**

```bash
# Generate a CIMD document
fastmcp auth cimd create --name "My App" \
  --redirect-uri "http://localhost:*/callback" \
  --client-id "https://myapp.example.com/oauth/client.json" \
  --output client.json

# Validate a hosted document
fastmcp auth cimd validate https://myapp.example.com/oauth/client.json
```

**Server-side support:**

CIMD is enabled by default on `OAuthProxy` and its provider subclasses (GitHub, Google, etc.). The server-side implementation includes SSRF-hardened document fetching with DNS pinning, dual redirect URI validation (both CIMD document patterns and proxy patterns must match), HTTP cache-aware revalidation, and `private_key_jwt` assertion validation for clients that need stronger authentication than public client auth.

Key details:
- CIMD URLs must be HTTPS with a non-root path
- `token_endpoint_auth_method` limited to `none` or `private_key_jwt` (no shared secrets)
- `redirect_uris` in CIMD documents support wildcard port patterns (`http://localhost:*/callback`)
- Servers fetch and cache documents with standard HTTP caching (ETag, Last-Modified, Cache-Control)
- CIMD is a protocol-level feature — any auth provider implementing the spec can support it

Documentation: [CIMD Authentication](/clients/auth/cimd), [OAuth Proxy CIMD config](/servers/auth/oauth-proxy#cimd-support)

### Pre-Registered OAuth Clients

The `OAuth` client helper now accepts `client_id` and `client_secret` parameters for servers where the client is already registered ([#3086](https://github.com/PrefectHQ/fastmcp/pull/3086)). This bypasses Dynamic Client Registration entirely — useful when DCR is disabled, or when the server has pre-provisioned credentials for your application.

```python
from fastmcp import Client
from fastmcp.client.auth import OAuth

async with Client(
    "https://mcp-server.example.com/mcp",
    auth=OAuth(
        client_id="my-registered-app",
        client_secret="my-secret",
        scopes=["read", "write"],
    ),
) as client:
    await client.ping()
```

The static credentials are injected before the OAuth flow begins, so the client never attempts DCR. If the server rejects the credentials, the error surfaces immediately rather than retrying with fresh registration (which can't help for fixed credentials). Public clients can omit `client_secret`.

Documentation: [Pre-Registered Clients](/clients/auth/oauth#pre-registered-clients)

### CLI: `fastmcp generate-cli`

`fastmcp generate-cli` connects to any MCP server, reads its tool schemas, and writes a standalone Python CLI script where every tool becomes a typed subcommand with flags, help text, and tab completion ([#3065](https://github.com/PrefectHQ/fastmcp/pull/3065)). The insight is that MCP tool schemas already contain everything a CLI framework needs — parameter names, types, descriptions, required/optional status — so the generator maps JSON Schema directly into [cyclopts](https://cyclopts.readthedocs.io/) commands.

```bash
# Generate from any server spec
fastmcp generate-cli weather
fastmcp generate-cli http://localhost:8000/mcp
fastmcp generate-cli server.py my_weather_cli.py

# Use the generated script
python my_weather_cli.py call-tool get_forecast --city London --days 3
python my_weather_cli.py list-tools
python my_weather_cli.py read-resource docs://readme
```

The generated script embeds the resolved transport (URL or stdio command), so it's self-contained — users don't need to know about MCP or FastMCP to use it. Supports `-f` to overwrite existing files, and name-based resolution via `fastmcp discover`.

Documentation: [Generate CLI](/cli/generate-cli)

### CLI: Goose Integration

New `fastmcp install goose` command that generates a `goose://extension?...` deeplink URL and opens it, prompting Goose to install the server as a STDIO extension ([#3040](https://github.com/PrefectHQ/fastmcp/pull/3040)). Goose requires `uvx` rather than `uv run`, so the command builds the appropriate invocation automatically.

```bash
fastmcp install goose server.py
fastmcp install goose server.py --with pandas --python 3.11
```

Also adds a full integration guide at [Goose Integration](/integrations/goose).

### ResponseLimitingMiddleware

New middleware for controlling tool response sizes, preventing large outputs from overwhelming LLM context windows ([#3072](https://github.com/PrefectHQ/fastmcp/pull/3072)). Text responses are truncated at UTF-8 character boundaries; structured responses (tools with `output_schema`) raise `ToolError` since truncation would corrupt the schema.

```python
from fastmcp.server.middleware.response_limiting import ResponseLimitingMiddleware

# Limit all tool responses to 500KB
mcp.add_middleware(ResponseLimitingMiddleware(max_size=500_000))

# Limit only specific tools, raise errors instead of truncating
mcp.add_middleware(ResponseLimitingMiddleware(
    max_size=100_000,
    tools=["search", "fetch_data"],
    raise_on_unstructured=True,
))
```

Key features:
- Configurable size limit (default 1MB)
- Tool-specific filtering via `tools` parameter
- Size metadata added to result's `meta` field for monitoring
- Configurable `raise_on_structured` and `raise_on_unstructured` behavior

Documentation: [Middleware](/servers/middleware)

### Background Task Context (SEP-1686)

`Context` now works transparently in background tasks running in Docket workers ([#2905](https://github.com/PrefectHQ/fastmcp/pull/2905)). Previously, tools running as background tasks couldn't use `ctx.elicit()` because there was no active request context. Now, when a tool executes in a Docket worker, `Context` detects this via its `task_id` and routes elicitation through Redis-based coordination: the task sets its status to `input_required`, sends a `notifications/tasks/updated` notification with elicitation metadata, and waits for the client to respond via `tasks/sendInput`.

```python
@mcp.tool(task=True)
async def interactive_task(ctx: Context) -> str:
    # Works transparently in both foreground and background task modes
    result = await ctx.elicit("Please provide additional input", str)

    if isinstance(result, AcceptedElicitation):
        return f"You provided: {result.data}"
    else:
        return "Elicitation was declined or cancelled"
```

`ctx.is_background_task` and `ctx.task_id` are available for tools that need to branch on execution mode.

### `require_auth` Removed

The `require_auth` authorization check introduced in beta1 has been removed in favor of scope-based authorization via `require_scopes` ([#3103](https://github.com/PrefectHQ/fastmcp/pull/3103)). Since configuring an `AuthProvider` already rejects unauthenticated requests at the transport level, `require_auth` was redundant — `require_scopes` provides the same guarantee with better granularity. The beta1 Component Authorization section has been updated to reflect this.

### MCP Apps (SDK Compatibility)

Support for [MCP Apps](https://modelcontextprotocol.io/specification/2025-06-18/server/apps) — the spec extension that lets MCP servers deliver interactive UIs via sandboxed iframes. Extension negotiation, typed UI metadata on tools and resources, and the `ui://` resource scheme. No component DSL, renderer, or `FastMCPApp` class yet — those are future phases.

**Breaking change from beta 2:** The `ui=` parameter on `@mcp.tool()` and `@mcp.resource()` has been renamed to `app=`, and the `ToolUI`/`ResourceUI` classes have been consolidated into a single `AppConfig` class. This follows the established `task=True`/`TaskConfig` pattern. The wire format (`meta["ui"]`, `_meta.ui`) is unchanged.

**Registering tools with app metadata:**

```python
from fastmcp import FastMCP
from fastmcp.apps import AppConfig, ResourceCSP, ResourcePermissions

mcp = FastMCP("My Server")

# Register the HTML bundle as a ui:// resource with CSP
@mcp.resource(
    "ui://my-app/view.html",
    app=AppConfig(
        csp=ResourceCSP(resource_domains=["https://unpkg.com"]),
        permissions=ResourcePermissions(clipboard_write={}),
    ),
)
def app_html() -> str:
    from pathlib import Path
    return Path("./dist/index.html").read_text()

# Tool with UI — clients render an iframe alongside the result
@mcp.tool(app=AppConfig(resource_uri="ui://my-app/view.html"))
async def list_users() -> list[dict]:
    return [{"id": "1", "name": "Alice"}]

# App-only tool — visible to the UI but hidden from the model
@mcp.tool(app=AppConfig(resource_uri="ui://my-app/view.html", visibility=["app"]))
async def delete_user(id: str) -> dict:
    return {"deleted": True}
```

The `app=` parameter accepts `True` (enable with defaults), an `AppConfig` instance, or a raw dict for forward compatibility. It merges into `meta["ui"]` — alongside any other metadata you set.

**`ui://` resources** automatically get the correct MIME type (`text/html;profile=mcp-app`) unless you override it explicitly.

**Extension negotiation**: The server advertises `io.modelcontextprotocol/ui` in `capabilities.extensions`. UI metadata (`_meta.ui`) always flows through to clients — the MCP Apps spec assigns visibility enforcement to the host, not the server. Tools can check whether the connected client supports a given extension at runtime via `ctx.client_supports_extension()`:

```python
from fastmcp import Context
from fastmcp.apps import AppConfig, UI_EXTENSION_ID

@mcp.tool(app=AppConfig(resource_uri="ui://dashboard"))
async def dashboard(ctx: Context) -> dict:
    data = compute_dashboard()
    if ctx.client_supports_extension(UI_EXTENSION_ID):
        return data
    return {"summary": format_text(data)}
```

**Key details:**
- `AppConfig` fields: `resource_uri`, `visibility`, `csp`, `permissions`, `domain`, `prefers_border` (all optional). On resources, `resource_uri` and `visibility` are validated as not-applicable and will raise `ValueError` if set.
- `csp` accepts a `ResourceCSP` model with structured domain lists: `connect_domains`, `resource_domains`, `frame_domains`, `base_uri_domains`
- `permissions` accepts a `ResourcePermissions` model: `camera`, `microphone`, `geolocation`, `clipboard_write` (each set to `{}` to request)
- `AppConfig` uses `extra="allow"` for forward compatibility with future spec additions
- Models use Pydantic aliases for wire format (`resourceUri`, `prefersBorder`, `connectDomains`, `clipboardWrite`)
- Resource metadata (including CSP/permissions) is propagated to `resources/read` response content items so hosts can read it when rendering the iframe
- `ctx.client_supports_extension(id)` is a general-purpose method — works for any extension, not just MCP Apps
- `structuredContent` in tool results already works via `ToolResult` — MCP Apps clients use this to pass data into the iframe
- The server does not strip `_meta.ui` for non-UI clients; per the spec, visibility enforcement is the host's responsibility

**Future phases** will add a component DSL for building UIs declaratively, an in-repo renderer, and a `FastMCPApp` class.

Implementation: `fastmcp_slim/fastmcp/server/apps.py` (models and constants), with integration points in `server.py` (decorator parameters), `low_level.py` (extension advertisement), and `context.py` (`client_supports_extension` method).

---

## 3.0.0beta1

### Provider-Based Architecture

v3.0 introduces a provider-based component system that replaces v2's static-only registration ([#2622](https://github.com/PrefectHQ/fastmcp/pull/2622)). Providers dynamically source tools, resources, templates, and prompts at runtime.

**Core abstraction** (`fastmcp_slim/fastmcp/server/providers/base.py`):
```python
class Provider:
    async def list_tools(self) -> Sequence[Tool]: ...
    async def get_tool(self, name: str) -> Tool | None: ...
    async def list_resources(self) -> Sequence[Resource]: ...
    async def get_resource(self, uri: str) -> Resource | None: ...
    async def list_resource_templates(self) -> Sequence[ResourceTemplate]: ...
    async def get_resource_template(self, uri: str) -> ResourceTemplate | None: ...
    async def list_prompts(self) -> Sequence[Prompt]: ...
    async def get_prompt(self, name: str) -> Prompt | None: ...
```

Providers support:
- **Lifecycle management**: `async def lifespan()` for setup/teardown
- **Visibility control**: `enable()` / `disable()` with name, version, tags, components, and allowlist mode
- **Transform stacking**: `provider.add_transform(Namespace(...))`, `provider.add_transform(ToolTransform(...))`

### LocalProvider

`LocalProvider` (`fastmcp_slim/fastmcp/server/providers/local_provider.py`) manages components registered via decorators. Can be used standalone and attached to multiple servers:

```python
from fastmcp.server.providers import LocalProvider

provider = LocalProvider()

@provider.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

# Attach to multiple servers
server1 = FastMCP("Server1", providers=[provider])
server2 = FastMCP("Server2", providers=[provider])
```

### ProxyProvider

`ProxyProvider` (`fastmcp_slim/fastmcp/server/providers/proxy.py`) proxies components from remote MCP servers via a client factory. Used by `create_proxy()` and `FastMCP.mount()` for remote server integration.

```python
from fastmcp.server import create_proxy

# Create proxy to remote server
server = create_proxy("http://remote-server/mcp")
```

### OpenAPIProvider

`OpenAPIProvider` (`fastmcp_slim/fastmcp/server/providers/openapi/provider.py`) creates MCP components from OpenAPI specifications. Routes map HTTP operations to tools, resources, or templates based on configurable rules.

```python
from fastmcp.server.providers.openapi import OpenAPIProvider
import httpx

client = httpx.AsyncClient(base_url="https://api.example.com")
provider = OpenAPIProvider(openapi_spec=spec, client=client)

mcp = FastMCP("API Server", providers=[provider])
```

Features:
- Automatic route-to-component mapping (GET → resource, POST/PUT/DELETE → tool)
- Custom route mappings via `route_maps` or `route_map_fn`
- Component customization via `mcp_component_fn`
- Name collision detection and handling

### FastMCPProvider

`FastMCPProvider` (`fastmcp_slim/fastmcp/server/providers/fastmcp_provider.py`) wraps a FastMCP server to enable mounting one server onto another. Components delegate execution through the wrapped server's middleware chain.

```python
from fastmcp import FastMCP
from fastmcp.server.providers import FastMCPProvider
from fastmcp.server.transforms import Namespace

main = FastMCP("Main")
sub = FastMCP("Sub")

@sub.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

# Mount with namespace
provider = FastMCPProvider(sub)
provider.add_transform(Namespace("sub"))
main.add_provider(provider)
# Tool accessible as "sub_greet"
```

### Transforms

Transforms modify components (tools, resources, prompts) as they flow from providers to clients ([#2836](https://github.com/PrefectHQ/fastmcp/pull/2836)). They use a middleware pattern where each transform receives a `call_next` callable to continue the chain.

**Built-in transforms** (`fastmcp_slim/fastmcp/server/transforms/`):

- `Namespace` - adds prefixes to names (`tool` → `api_tool`) and path segments to URIs (`data://x` → `data://api/x`)
- `ToolTransform` - modifies tool schemas (rename, description, tags, argument transforms)
- `Visibility` - sets visibility state on components by key or tag (backs `enable()`/`disable()` API)
- `VersionFilter` - filters components by version range (`version_gte`, `version_lt`)
- `ResourcesAsTools` - exposes resources as tools for tool-only clients
- `PromptsAsTools` - exposes prompts as tools for tool-only clients

```python
from fastmcp.server.transforms import Namespace, ToolTransform
from fastmcp.tools.tool_transform import ToolTransformConfig

provider = SomeProvider()
provider.add_transform(Namespace("api"))
provider.add_transform(ToolTransform({
    "api_verbose_tool_name": ToolTransformConfig(name="short")
}))

# Stacking composes transformations
# "foo" → "api_foo" (namespace) → "short" (rename)
```

**Custom transforms** subclass `Transform` and override needed methods:

```python
from collections.abc import Sequence
from fastmcp.server.transforms import Transform, GetToolNext
from fastmcp.tools import Tool

class TagFilter(Transform):
    def __init__(self, required_tags: set[str]):
        self.required_tags = required_tags

    async def list_tools(self, tools: Sequence[Tool]) -> Sequence[Tool]:
        return [t for t in tools if t.tags & self.required_tags]

    async def get_tool(self, name: str, call_next: GetToolNext) -> Tool | None:
        tool = await call_next(name)
        return tool if tool and tool.tags & self.required_tags else None
```

Transforms apply at two levels:
- **Provider-level**: `provider.add_transform()` - affects only that provider's components
- **Server-level**: `server.add_transform()` - affects all components from all providers

Documentation: `docs/servers/transforms/transforms.mdx`, `docs/servers/visibility.mdx`

### ResourcesAsTools and PromptsAsTools

These transforms expose resources and prompts as tools for clients that only support the tools protocol. Each transform generates two tools that provide listing and access functionality.

**ResourcesAsTools** generates `list_resources` and `read_resource` tools:

```python
from fastmcp import FastMCP
from fastmcp.server.transforms import ResourcesAsTools

mcp = FastMCP("Server")

@mcp.resource("data://config")
def get_config() -> dict:
    return {"setting": "value"}

mcp.add_transform(ResourcesAsTools(mcp))
# Now has list_resources and read_resource tools
```

The `list_resources` tool returns JSON with resource metadata. The `read_resource` tool accepts a URI and returns the resource content, preserving both text and binary data through base64 encoding.

**PromptsAsTools** generates `list_prompts` and `get_prompt` tools:

```python
from fastmcp import FastMCP
from fastmcp.server.transforms import PromptsAsTools

mcp = FastMCP("Server")

@mcp.prompt
def analyze_code(code: str, language: str = "python") -> str:
    return f"Analyze this {language} code:\n{code}"

mcp.add_transform(PromptsAsTools(mcp))
# Now has list_prompts and get_prompt tools
```

The `list_prompts` tool returns JSON with prompt metadata including argument information. The `get_prompt` tool accepts a prompt name and optional arguments dict, returning the rendered prompt as a messages array. Non-text content (like embedded resources) is preserved as structured JSON.

Both transforms:
- Capture a provider reference at construction for deferred querying
- Route through `FastMCP.read_resource()` / `FastMCP.render_prompt()` when the provider is FastMCP, ensuring middleware chains execute
- Fall back to direct provider methods for plain providers
- Return JSON for easy parsing by tool-only clients

Documentation: `docs/servers/transforms/resources-as-tools.mdx`, `docs/servers/transforms/prompts-as-tools.mdx`

---

### Session-Scoped State

v3.0 changes context state from request-scoped to session-scoped. State now persists across multiple tool calls within the same MCP session.

```python
@mcp.tool
async def increment_counter(ctx: Context) -> int:
    count = await ctx.get_state("counter") or 0
    await ctx.set_state("counter", count + 1)
    return count + 1
```

State is automatically keyed by session ID, ensuring isolation between different clients. The implementation uses [pykeyvalue](https://github.com/strawgate/py-key-value) for pluggable storage backends:

```python
from key_value.aio.stores.redis import RedisStore

# Use Redis for distributed deployments
mcp = FastMCP("server", session_state_store=RedisStore(...))
```

**Key details:**
- Methods are now async: `await ctx.get_state()`, `await ctx.set_state()`, `await ctx.delete_state()`
- State expires after 1 day (TTL) to prevent unbounded memory growth
- Works during `on_initialize` middleware when using the same session object
- For distributed HTTP, session identity comes from the `mcp-session-id` header

Documentation: `docs/servers/context.mdx`

---

### Visibility System

Components can be enabled/disabled using the visibility system. Each `enable()` or `disable()` call adds a stateless Visibility transform that marks components via internal metadata. Later transforms override earlier ones.

```python
mcp = FastMCP("Server")

# Disable by name and component type
mcp.disable(names={"dangerous_tool"}, components=["tool"])

# Disable by tag
mcp.disable(tags={"admin"})

# Disable by version
mcp.disable(names={"old_tool"}, version="1.0", components=["tool"])

# Allowlist mode - only show components with these tags
mcp.enable(tags={"public"}, only=True)

# Enable overrides earlier disable (later transform wins)
mcp.disable(tags={"internal"})
mcp.enable(names={"safe_tool"})  # safe_tool is visible despite internal tag
```

Works at both server and provider level. Supports:
- **Blocklist mode** (default): All components visible except explicitly disabled
- **Allowlist mode** (`only=True`): Only explicitly enabled components visible
- **Tag-based filtering**: Enable/disable groups of components by tag
- **Override semantics**: Later transforms override earlier marks (enable after disable = enabled)
- **Transform ordering**: Visibility transforms are injected at the point you call them, so component state is known

#### Per-Session Visibility

Server-level visibility changes affect all connected clients. For per-session control, use `Context` methods that apply rules only to the current session ([#2917](https://github.com/PrefectHQ/fastmcp/pull/2917)):

```python
from fastmcp import FastMCP
from fastmcp.server.context import Context

mcp = FastMCP("Server")

@mcp.tool(tags={"premium"})
def premium_analysis(data: str) -> str:
    return f"Premium analysis of: {data}"

@mcp.tool
async def unlock_premium(ctx: Context) -> str:
    """Unlock premium features for this session only."""
    await ctx.enable_components(tags={"premium"})
    return "Premium features unlocked"

@mcp.tool
async def reset_features(ctx: Context) -> str:
    """Reset to default feature set."""
    await ctx.reset_visibility()
    return "Features reset to defaults"

# Globally disabled - sessions unlock individually
mcp.disable(tags={"premium"})
```

Session visibility methods:
- `await ctx.enable_components(...)`: Enable components for this session
- `await ctx.disable_components(...)`: Disable components for this session
- `await ctx.reset_visibility()`: Clear session rules, return to global defaults

Session rules override global transforms. FastMCP automatically sends `ToolListChangedNotification` (and resource/prompt equivalents) to affected sessions when visibility changes.

Documentation: `docs/servers/visibility.mdx`

---

### Component Versioning

v3.0 introduces versioning support for tools, resources, and prompts. Components can declare a version, and when multiple versions of the same component exist, the highest version is automatically exposed to clients.

**Declaring versions:**

```python
@mcp.tool(version="1.0")
def add(x: int, y: int) -> int:
    return x + y

@mcp.tool(version="2.0")
def add(x: int, y: int, z: int = 0) -> int:
    return x + y + z

# Only v2.0 is exposed to clients via list_tools()
# Calling "add" invokes the v2.0 implementation
```

**Version comparison:**
- Uses PEP 440 semantic versioning (1.10 > 1.9 > 1.2)
- Falls back to string comparison for non-PEP 440 versions (dates like `2025-01-15` work)
- Unversioned components sort lower than any versioned component
- The `v` prefix is normalized (`v1.0` equals `1.0`)

**Version visibility in meta:**

List operations expose all available versions in the component's `meta` field:

```python
tools = await client.list_tools()
# Each tool's meta includes:
# - meta["fastmcp"]["version"]: the version of this component ("2.0")
# - meta["fastmcp"]["versions"]: all available versions ["2.0", "1.0"]
```

**Retrieving and calling specific versions:**

```python
# Get the highest version (default)
tool = await server.get_tool("add")

# Get a specific version
tool_v1 = await server.get_tool("add", version="1.0")

# Call a specific version
result = await server.call_tool("add", {"x": 1, "y": 2}, version="1.0")
```

**Client version requests:**

The FastMCP client supports version selection:

```python
async with Client(server) as client:
    # Call specific tool version
    result = await client.call_tool("add", {"x": 1, "y": 2}, version="1.0")

    # Get specific prompt version
    prompt = await client.get_prompt("my_prompt", {"text": "..."}, version="2.0")
```

For generic MCP clients, pass version via `_meta` in arguments:

```json
{
  "x": 1,
  "y": 2,
  "_meta": {
    "fastmcp": {
      "version": "1.0"
    }
  }
}
```

**VersionFilter transform:**

The `VersionFilter` transform enables serving different API versions from a single codebase:

```python
from fastmcp import FastMCP
from fastmcp.server.providers import LocalProvider
from fastmcp.server.transforms import VersionFilter

# Define components on a shared provider
components = LocalProvider()

@components.tool(version="1.0")
def calculate(x: int, y: int) -> int:
    return x + y

@components.tool(version="2.0")
def calculate(x: int, y: int, z: int = 0) -> int:
    return x + y + z

# Create servers that share the provider with different filters
api_v1 = FastMCP("API v1", providers=[components])
api_v1.add_transform(VersionFilter(version_lt="2.0"))

api_v2 = FastMCP("API v2", providers=[components])
api_v2.add_transform(VersionFilter(version_gte="2.0"))
```

Parameters mirror comparison operators:
- `version_gte`: Versions >= this value pass through
- `version_lt`: Versions < this value pass through

**Key format:**

Component keys now include a version suffix using `@` as a delimiter:
- Versioned: `tool:add@1.0`, `resource:data://config@2.0`
- Unversioned: `tool:add@`, `resource:data://config@`

The `@` is always present (even for unversioned components) to enable unambiguous parsing of URIs that may contain `@`.

---

### Type-Safe Canonical Results

v3.0 introduces type-safe result classes that provide explicit control over component responses while supporting MCP runtime metadata: `ToolResult` ([#2736](https://github.com/PrefectHQ/fastmcp/pull/2736)), `ResourceResult` ([#2734](https://github.com/PrefectHQ/fastmcp/pull/2734)), and `PromptResult` ([#2738](https://github.com/PrefectHQ/fastmcp/pull/2738)).

#### ToolResult

`ToolResult` (`fastmcp_slim/fastmcp/tools/tool.py:79`) provides structured tool responses:

```python
from fastmcp.tools import ToolResult

@mcp.tool
def process(data: str) -> ToolResult:
    return ToolResult(
        content=[TextContent(type="text", text="Done")],
        structured_content={"status": "success", "count": 42},
        meta={"processing_time_ms": 150}
    )
```

Fields:
- `content`: List of MCP ContentBlocks (text, images, etc.)
- `structured_content`: Dict matching tool's output schema
- `meta`: Runtime metadata passed to MCP as `_meta`

#### ResourceResult

`ResourceResult` (`fastmcp_slim/fastmcp/resources/resource.py:117`) provides structured resource responses:

```python
from fastmcp.resources import ResourceResult, ResourceContent

@mcp.resource("data://items")
def get_items() -> ResourceResult:
    return ResourceResult(
        contents=[
            ResourceContent({"key": "value"}),  # auto-serialized to JSON
            ResourceContent(b"binary data"),
        ],
        meta={"count": 2}
    )
```

Accepts strings, bytes, or `list[ResourceContent]` for flexible content handling.

#### PromptResult

`PromptResult` (`fastmcp_slim/fastmcp/prompts/prompt.py:109`) provides structured prompt responses:

```python
from fastmcp.prompts import PromptResult, Message

@mcp.prompt
def conversation() -> PromptResult:
    return PromptResult(
        messages=[
            Message("What's the weather?"),
            Message("It's sunny today.", role="assistant"),
        ],
        meta={"generated_at": "2024-01-01"}
    )
```

---

### Background Tasks (SEP-1686)

v3.0 implements MCP SEP-1686 for background task execution via Docket integration.

**Configuration** (`fastmcp_slim/fastmcp/server/tasks/config.py`):

```python
from fastmcp.server.tasks import TaskConfig

@mcp.tool(task=TaskConfig(mode="required"))
async def long_running_task():
    # Must be executed as background task
    ...

@mcp.tool(task=TaskConfig(mode="optional"))
async def flexible_task():
    # Supports both sync and task execution
    ...

@mcp.tool(task=True)  # Shorthand for mode="optional"
async def simple_task():
    ...
```

Task modes:
- `"forbidden"`: Component does not support task execution (default)
- `"optional"`: Supports both synchronous and task execution
- `"required"`: Must be executed as background task

Requires Docket server for task scheduling and result polling.

---

### Decorators Return Functions

v3.0 changes what decorators (`@tool`, `@resource`, `@prompt`) return ([#2856](https://github.com/PrefectHQ/fastmcp/pull/2856)). Decorators now return the original function unchanged, rather than transforming it into a component object.

**v3 behavior (default):**
```python
@mcp.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

# greet is still your function - call it directly
greet("World")  # "Hello, World!"
```

**Why this matters:**
- Functions stay callable - useful for testing and reuse
- Instance methods just work: `mcp.add_tool(obj.method)`
- Matches how Flask, FastAPI, and Typer decorators behave

**For v2 compatibility:**

```python
import fastmcp

# v2 behavior: decorators return FunctionTool/FunctionResource/FunctionPrompt objects
fastmcp.settings.decorator_mode = "object"
```

Environment variable: `FASTMCP_DECORATOR_MODE=object`

---

### CLI Auto-Reload

The `--reload` flag enables file watching with automatic server restarts for development ([#2816](https://github.com/PrefectHQ/fastmcp/pull/2816)).

```bash
# Watch for changes and restart
fastmcp run server.py --reload

# Watch specific directories
fastmcp run server.py --reload --reload-dir ./src --reload-dir ./lib

# Works with any transport
fastmcp run server.py --reload --transport http --port 8080
```

Implementation (`fastmcp_slim/fastmcp/cli/run.py`):
- Uses `watchfiles` for efficient file monitoring
- Runs server as subprocess for clean restarts
- Stateless mode for seamless reconnection after restart
- stdio: Full MCP features including elicitation
- HTTP: Limited bidirectional features during reload

Also available with `fastmcp dev inspector`:
```bash
fastmcp dev inspector server.py  # Includes --reload by default
```

---

### Component Authorization

v3.0 introduces callable-based authorization for tools, resources, and prompts ([#2855](https://github.com/PrefectHQ/fastmcp/pull/2855)).

**Component-level auth**:

```python
from fastmcp import FastMCP
from fastmcp.server.auth import require_scopes

mcp = FastMCP()

@mcp.tool(auth=require_scopes("write"))
def protected_tool(): ...

@mcp.resource("data://secret", auth=require_scopes("read"))
def secret_data(): ...

@mcp.prompt(auth=require_scopes("admin"))
def admin_prompt(): ...
```

**Server-wide auth via middleware**:

```python
from fastmcp.server.middleware import AuthMiddleware
from fastmcp.server.auth import require_scopes, restrict_tag

# Require specific scope for all components
mcp = FastMCP(middleware=[AuthMiddleware(auth=require_scopes("api"))])

# Tag-based restrictions
mcp = FastMCP(middleware=[
    AuthMiddleware(auth=restrict_tag("admin", scopes=["admin"]))
])
```

Built-in checks:
- `require_scopes(*scopes)`: Requires specific OAuth scopes
- `restrict_tag(tag, scopes)`: Requires scopes only for tagged components

Custom checks receive `AuthContext` with `token` and `component`:

```python
def custom_check(ctx: AuthContext) -> bool:
    return ctx.token is not None and "admin" in ctx.token.scopes
```

STDIO transport bypasses all auth checks (no OAuth concept).

---

### FileSystemProvider

v3.0 introduces `FileSystemProvider`, a fundamentally different approach to organizing MCP servers. Instead of importing a server instance and decorating functions with `@server.tool`, you use standalone decorators in separate files and let the provider discover them.

**The problem it solves**: Traditional servers require coordination between files—either tool files import the server (creating coupling) or the server imports all tool modules (creating a registry bottleneck). FileSystemProvider removes this coupling entirely.

**Usage** ([#2823](https://github.com/PrefectHQ/fastmcp/pull/2823)):

```python
from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider

# Scans mcp/ directory for decorated functions
mcp = FastMCP("server", providers=[FileSystemProvider("mcp/")])
```

**Tool files are self-contained**:

```python
# mcp/tools/greet.py
from fastmcp.tools import tool

@tool
def greet(name: str) -> str:
    """Greet someone by name."""
    return f"Hello, {name}!"
```

Features:
- **Standalone decorators**: `@tool`, `@resource`, `@prompt` from `fastmcp.tools`, `fastmcp.resources`, `fastmcp.prompts` ([#2832](https://github.com/PrefectHQ/fastmcp/pull/2832))
- **Reload mode**: `FileSystemProvider("mcp/", reload=True)` re-scans on every request for development
- **Package support**: Directories with `__init__.py` support relative imports
- **Warning deduplication**: Broken imports warn once per file modification

Documentation: [FileSystemProvider](/servers/providers/filesystem)

---

### SkillsProvider

v3.0 introduces `SkillsProvider` for exposing agent skills as MCP resources ([#2944](https://github.com/PrefectHQ/fastmcp/pull/2944)). Skills are directories containing instructions and supporting files that teach AI assistants how to perform tasks—used by Claude Code, Cursor, VS Code Copilot, and other AI coding tools.

**Usage**:

```python
from pathlib import Path
from fastmcp import FastMCP
from fastmcp.server.providers.skills import SkillsDirectoryProvider

mcp = FastMCP("Skills Server")
mcp.add_provider(SkillsDirectoryProvider(roots=Path.home() / ".claude" / "skills"))
```

Each subdirectory with a `SKILL.md` file becomes a discoverable skill. Clients see:
- `skill://{name}/SKILL.md` - Main instruction file
- `skill://{name}/_manifest` - JSON listing of all files with sizes and hashes
- `skill://{name}/{path}` - Supporting files (via template or resources)

**Two-layer architecture**:
- `SkillProvider` - Handles a single skill folder
- `SkillsDirectoryProvider` - Scans directories, creates a `SkillProvider` per valid skill

**Vendor providers** with locked default paths:

| Provider | Directory |
|----------|-----------|
| `ClaudeSkillsProvider` | `~/.claude/skills/` |
| `CursorSkillsProvider` | `~/.cursor/skills/` |
| `VSCodeSkillsProvider` | `~/.copilot/skills/` |
| `CodexSkillsProvider` | `/etc/codex/skills/`, `~/.codex/skills/` |
| `GeminiSkillsProvider` | `~/.gemini/skills/` |
| `GooseSkillsProvider` | `~/.config/agents/skills/` |
| `CopilotSkillsProvider` | `~/.copilot/skills/` |
| `OpenCodeSkillsProvider` | `~/.config/opencode/skills/` |

**Progressive disclosure**: By default, supporting files are hidden from `list_resources()` and accessed via template. Set `supporting_files="resources"` for full enumeration.

Documentation: [Skills Provider](/servers/providers/skills)

---

### OpenTelemetry Tracing

v3.0 adds OpenTelemetry instrumentation for observability into server and client operations ([#2869](https://github.com/PrefectHQ/fastmcp/pull/2869)).

**Server spans**: Created for tool calls, resource reads, and prompt renders with attributes including component key, provider type, session ID, and auth context.

**Client spans**: Wrap outgoing calls with W3C trace context propagation via request meta.

```python
# Tracing is passive - configure an OTel SDK to export spans
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter

provider = TracerProvider()
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)

# Use fastmcp normally - spans export to your configured backend
```

Components provide their own span attributes through a `get_span_attributes()` method that subclasses override—this lets LocalProvider, FastMCPProvider, and ProxyProvider each include relevant context (original names, backend URIs, etc.).

Documentation: [Telemetry](/servers/telemetry)

---

### Pagination

v3.0 adds pagination support for list operations when servers expose many components ([#2903](https://github.com/PrefectHQ/fastmcp/pull/2903)).

```python
from fastmcp import FastMCP

# Enable pagination with 50 items per page
server = FastMCP("ComponentRegistry", list_page_size=50)
```

When `list_page_size` is set, `tools/list`, `resources/list`, `resources/templates/list`, and `prompts/list` paginate responses with `nextCursor` for subsequent pages.

**Client behavior**: The FastMCP Client fetches all pages automatically—`list_tools()` and similar methods return the complete list. For manual pagination (memory constraints, progress reporting), use `_mcp` variants:

```python
async with Client(server) as client:
    result = await client.list_tools_mcp()
    while result.nextCursor:
        result = await client.list_tools_mcp(cursor=result.nextCursor)
```

Documentation: [Pagination](/servers/pagination)

---

### Composable Lifespans

Lifespans can be combined with the `|` operator for modular setup/teardown ([#2828](https://github.com/PrefectHQ/fastmcp/pull/2828)):

```python
from fastmcp import FastMCP
from fastmcp.server.lifespan import lifespan

@lifespan
async def db_lifespan(server):
    db = await connect_db()
    try:
        yield {"db": db}
    finally:
        await db.close()

@lifespan
async def cache_lifespan(server):
    cache = await connect_cache()
    try:
        yield {"cache": cache}
    finally:
        await cache.close()

mcp = FastMCP("server", lifespan=db_lifespan | cache_lifespan)
```

Both enter lifespans in order and exit in reverse (LIFO). Context dicts are merged.

Also adds `combine_lifespans()` utility for FastAPI integration:

```python
from fastmcp.utilities.lifespan import combine_lifespans

app = FastAPI(lifespan=combine_lifespans(app_lifespan, mcp_app.lifespan))
```

Documentation: [Lifespan](/servers/lifespan)

---

### Tool Timeout

Tools can limit foreground execution time with a `timeout` parameter ([#2872](https://github.com/PrefectHQ/fastmcp/pull/2872)):

```python
@mcp.tool(timeout=30.0)
async def fetch_data(url: str) -> dict:
    """Fetch with 30-second timeout."""
    ...
```

When exceeded, clients receive MCP error code `-32000`. Both sync and async tools are supported—sync functions run in thread pools so the timeout applies regardless of execution model.

Note: This timeout applies to foreground execution only. Background tasks (`task=True`) execute in Docket workers where this timeout isn't enforced.

---

### PingMiddleware

Sends periodic server-to-client pings to keep long-lived connections alive ([#2838](https://github.com/PrefectHQ/fastmcp/pull/2838)):

```python
from fastmcp import FastMCP
from fastmcp.server.middleware import PingMiddleware

mcp = FastMCP("server")
mcp.add_middleware(PingMiddleware(interval_ms=5000))
```

The middleware starts a background ping task on first message from each session, using the session's existing task group for automatic cleanup when the session ends.

---

### Context.transport Property

Tools can detect which transport is active ([#2850](https://github.com/PrefectHQ/fastmcp/pull/2850)):

```python
from fastmcp import FastMCP, Context

mcp = FastMCP("example")

@mcp.tool
def my_tool(ctx: Context) -> str:
    if ctx.transport == "stdio":
        return "short response"
    return "detailed response with more context"
```

Returns `Literal["stdio", "sse", "streamable-http"]` when running, or `None` outside a server context.

---

### Automatic Threadpool for Sync Functions

Synchronous tools, resources, and prompts now automatically run in a threadpool, preventing event loop blocking during concurrent requests ([#2865](https://github.com/PrefectHQ/fastmcp/pull/2865)):

```python
import time

@mcp.tool
def slow_tool():
    time.sleep(10)  # No longer blocks other requests
    return "done"
```

Three concurrent calls now execute in parallel (~10s) rather than sequentially (30s). Uses `anyio.to_thread.run_sync()` which properly propagates contextvars, so `Context` and `Depends` continue to work.

---

### CLI Update Notifications

The CLI notifies users when a newer FastMCP version is available on PyPI ([#2840](https://github.com/PrefectHQ/fastmcp/pull/2840)).

**Setting**: `FASTMCP_CHECK_FOR_UPDATES`
- `"stable"` - Check for stable releases (default)
- `"prerelease"` - Include alpha/beta/rc versions
- `"off"` - Disable

12-hour cache, 2-second timeout, fails silently on network errors.

---

### Deprecated Features

These emit deprecation warnings but continue to work.

#### Mount Prefix Parameter

The `prefix` parameter for `mount()` renamed to `namespace`:

```python
# Deprecated
main.mount(subserver, prefix="api")

# New
main.mount(subserver, namespace="api")
```

#### Tag Filtering, Tool Serializer, Tool Transformations Init Parameters

These constructor parameters have been **removed** (not just deprecated) as of rc1. See "Breaking: Deprecated `FastMCP()` Constructor Kwargs Removed" in the rc1 section above. The `add_tool_transformation()` and `remove_tool_transformation()` methods remain as deprecated shims.

---

### Breaking Changes

#### WSTransport Removed

The deprecated `WSTransport` client transport has been removed ([#2826](https://github.com/PrefectHQ/fastmcp/pull/2826)). Use `StreamableHttpTransport` instead.

#### Decorators Return Functions

Decorators (`@tool`, `@resource`, `@prompt`) now return the original function instead of component objects. Code that treats the decorated function as a `FunctionTool`, `FunctionResource`, or `FunctionPrompt` will break.

```python
# v2.x
@mcp.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

isinstance(greet, FunctionTool)  # True

# v3.0
@mcp.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

isinstance(greet, FunctionTool)  # False
callable(greet)                  # True - it's still your function
greet("World")                   # "Hello, World!"
```

Set `FASTMCP_DECORATOR_MODE=object` or `fastmcp.settings.decorator_mode = "object"` for v2 behavior.

#### Component Enable/Disable Moved to Server/Provider

The `enabled` field and `enable()`/`disable()` methods removed from component objects:

```python
# v2.x
tool = await server.get_tool("my_tool")
tool.disable()

# v3.0
server.disable(names={"my_tool"}, components=["tool"])
```

#### Component Lookup Methods

Server lookup and listing methods have updated signatures:

- Parameter names: `get_tool(name=...)`, `get_resource(uri=...)`, etc. (was `key`)
- Plural listing methods renamed: `get_tools()` → `list_tools()`, `get_resources()` → `list_resources()`, etc.
- Return types: `list_tools()`, `list_resources()`, etc. return lists instead of dicts

```python
# v2.x
tools = await server.get_tools()
tool = tools["my_tool"]

# v3.0
tools = await server.list_tools()
tool = next((t for t in tools if t.name == "my_tool"), None)
```

#### Prompt Return Types

Prompt functions now use `Message` instead of `mcp.types.PromptMessage`:

```python
# v2.x
from mcp.types import PromptMessage, TextContent

@mcp.prompt
def my_prompt() -> PromptMessage:
    return PromptMessage(role="user", content=TextContent(type="text", text="Hello"))

# v3.0
from fastmcp.prompts import Message

@mcp.prompt
def my_prompt() -> Message:
    return Message("Hello")  # role defaults to "user"
```

#### Auth Provider Environment Variables Removed

Auth providers no longer auto-load from environment variables ([#2752](https://github.com/PrefectHQ/fastmcp/pull/2752)):

```python
# v2.x - auto-loaded from FASTMCP_SERVER_AUTH_GITHUB_*
auth = GitHubProvider()

# v3.0 - explicit configuration
import os
auth = GitHubProvider(
    client_id=os.environ["GITHUB_CLIENT_ID"],
    client_secret=os.environ["GITHUB_CLIENT_SECRET"],
)
```

See `docs/development/v3-notes/auth-provider-env-vars.mdx` for rationale.

#### Server Banner Environment Variable

`FASTMCP_SHOW_CLI_BANNER` → `FASTMCP_SHOW_SERVER_BANNER` ([#2771](https://github.com/PrefectHQ/fastmcp/pull/2771))

Now applies to all server startup methods, not just the CLI.

#### Context State Methods Are Async

`ctx.set_state()` and `ctx.get_state()` are now async and session-scoped:

```python
# v2.x
ctx.set_state("key", "value")
value = ctx.get_state("key")

# v3.0
await ctx.set_state("key", "value")
value = await ctx.get_state("key")
```

State now persists across requests within a session. See "Session-Scoped State" above.
