Metadata-Version: 2.5
Name: gemini-research-mcp
Version: 0.16.0b1
Summary: MCP server for AI-powered research using Gemini: quick grounded search + Deep Research Agent
Project-URL: Homepage, https://github.com/machinemates-ai/gemini-research-mcp
Project-URL: Documentation, https://github.com/machinemates-ai/gemini-research-mcp#readme
Project-URL: Repository, https://github.com/machinemates-ai/gemini-research-mcp
Project-URL: Issues, https://github.com/machinemates-ai/gemini-research-mcp/issues
Author-email: Guillaume Fortaine <guillaume.fortaine+github@machinemates.ai>
License-Expression: MIT
License-File: LICENSE
Keywords: ai,deep-research,gemini,google-search,grounding,mcp,model-context-protocol,research
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Internet :: WWW/HTTP :: Indexing/Search
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Typing :: Typed
Requires-Python: >=3.12
Requires-Dist: fastmcp[tasks]==4.0.0b5
Requires-Dist: google-genai<3.0.0,>=2.20.0
Requires-Dist: httpx>=0.28.1
Requires-Dist: platformdirs>=4.5.1
Requires-Dist: py-key-value-aio[disk]<0.5.0,>=0.4.5
Requires-Dist: python-dotenv>=1.2.1
Provides-Extra: dev
Requires-Dist: marko>=2.2.2; extra == 'dev'
Requires-Dist: mypy>=1.10.0; extra == 'dev'
Requires-Dist: protego>=0.3.1; extra == 'dev'
Requires-Dist: pygments>=2.19.2; extra == 'dev'
Requires-Dist: pytest-asyncio>=0.23.0; extra == 'dev'
Requires-Dist: pytest-cov>=4.0.0; extra == 'dev'
Requires-Dist: pytest-timeout>=2.3.0; extra == 'dev'
Requires-Dist: pytest>=8.0.0; extra == 'dev'
Requires-Dist: python-docx>=1.2.0; extra == 'dev'
Requires-Dist: ruff>=0.4.0; extra == 'dev'
Requires-Dist: trafilatura>=2.0.0; extra == 'dev'
Requires-Dist: types-pygments>=2.19.0; extra == 'dev'
Provides-Extra: distributed
Requires-Dist: py-key-value-aio[redis]<0.5.0,>=0.4.5; extra == 'distributed'
Provides-Extra: docx
Requires-Dist: marko>=2.2.2; extra == 'docx'
Requires-Dist: pygments>=2.19.2; extra == 'docx'
Requires-Dist: python-docx>=1.2.0; extra == 'docx'
Provides-Extra: web
Requires-Dist: protego>=0.3.1; extra == 'web'
Requires-Dist: trafilatura>=2.0.0; extra == 'web'
Description-Content-Type: text/markdown

# Gemini Research MCP Server

[![PyPI version](https://img.shields.io/pypi/v/gemini-research-mcp.svg)](https://pypi.org/project/gemini-research-mcp/)
[![CI](https://github.com/machinemates-ai/gemini-research-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/machinemates-ai/gemini-research-mcp/actions/workflows/ci.yml)
[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

MCP server for AI-powered research using **Gemini**. Fast grounded search, URL extraction, comprehensive Deep Research, and session management.

Built on **FastMCP `4.0.0b5`** (beta, exact-pinned) with the modern sessionless
MCP protocol, **Gemini `3.7 Flash`**, MCP Tasks (SEP-1732), the guard-pattern
elicitation flow, a BM25-compacted tool catalog, and pluggable Disk/Redis
storage for multi-worker deployments.

## Architecture

![Architecture](https://raw.githubusercontent.com/machinemates-ai/gemini-research-mcp/main/docs/architecture.png)

<details>
<summary>Mermaid source</summary>

```mermaid
flowchart TB
    subgraph Client["MCP Client"]
        Claude["Claude / Copilot"]
    end

    subgraph Server["gemini-research-mcp"]
        direction TB
        FastMCP["FastMCP 4 Server<br/>@mcp.tool()<br/>BM25SearchTransform"]
        
        subgraph Tools["Tools"]
            RW["research_web<br/>Quick lookup 5-30s"]
            RD["research_deep<br/>Autonomous 3-20min"]
            RF["research_followup<br/>Continue session"]
            RR["resume_research<br/>Recover interrupted"]
            FW["fetch_webpage<br/>Content extraction"]
            EX["export_research_session<br/>MD/JSON/DOCX"]
            LS["list_research_sessions"]
            LT["list_format_templates"]
        end

        subgraph Modules["Core Modules"]
            Quick["quick.py<br/>Web grounding"]
            Deep["deep.py<br/>Deep research agent"]
            Content["content.py<br/>SSRF protection"]
            StorageMod["storage.py<br/>Session + artifact store"]
            Templates["templates.py<br/>Format templates"]
        end
    end

    subgraph External["External Services"]
        Gemini["Google Gemini API"]
        Web["Web Sources<br/>via trafilatura"]
    end

    subgraph Storage["Persistence"]
        Disk["DiskStore<br/>XDG data directory"]
        Redis["Redis/Valkey<br/>shared multi-worker storage"]
    end

    Claude -->|"MCP Protocol"| FastMCP
    FastMCP --> Tools
    
    RW --> Quick
    RD --> Deep
    RF --> StorageMod
    RR --> StorageMod
    FW --> Content
    LT --> Templates
    
    Quick -->|"grounding"| Gemini
    Deep -->|"agentic"| Gemini
    Content -->|"httpx"| Web
    StorageMod --> Disk
    StorageMod -.-> Redis
```

</details>

## Tools

The server exposes a **BM25-compacted catalog**: only the 5 tools below plus
the synthetic `search_tools`/`call_tool` pair are listed by default
(`fastmcp.server.transforms.search.BM25SearchTransform`). Utility tools
(`fetch_webpage`, `research_followup`, `list_research_sessions`,
`list_format_templates`, `refine_research_plan`,
`inspect_mcp_server_for_gemini`) are hidden from the default
listing to keep the catalog small for LLM tool-selection, but remain fully
callable directly by name or via the `call_tool` proxy, and are discoverable
by relevance through `search_tools`.

| Tool | Description | Latency | Visible by default |
|------|-------------|---------|---------------------|
| `research_web` | Fast web search with citations | 5-30 sec | ✅ |
| `research_deep` | Multi-step autonomous research (MCP Tasks) | 3-20 min | ✅ |
| `research_deep_max` | Maximum-comprehensiveness Deep Research for exhaustive/high-stakes work | longer-running | ✅ |
| `resume_research` | Resume interrupted/in-progress sessions | instant | ✅ |
| `export_research_session` | Disk-first export to persistent Markdown, JSON, or DOCX artifacts | instant | ✅ |
| `search_tools` | Discover hidden utility tools by relevance (BM25) | instant | ✅ |
| `call_tool` | Proxy to invoke any hidden tool by name | varies | ✅ |
| `research_followup` | Continue conversation after research | 5-30 sec | discoverable |
| `list_research_sessions` | List saved research sessions | instant | discoverable |
| `list_format_templates` | Browse report format templates | instant | discoverable |
| `refine_research_plan` | Iterate on or approve a `collaborative_planning=True` plan | instant-3min | discoverable |
| `fetch_webpage` | Extract article content from a specific URL (SSRF-protected, chunkable) | 0.5-2 sec | discoverable |
| `inspect_mcp_server_for_gemini` | Diagnose remote MCP schemas and allowed tool names | varies | discoverable |

### `research_deep` / `research_deep_max` Deep Research parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|--------------|
| `visualization` | `"off"` \| `"auto"` | `"off"` | Let the agent produce and persist supporting images/charts. Images are persisted as MCP resource artifacts (`research://exports/{id}`), never inlined as text. |
| `collaborative_planning` | boolean | `false` | Return the drafted research plan and an interaction ID instead of running the full report. Approve or iterate on the plan with `refine_research_plan(previous_interaction_id=..., decision="approve"|"iterate")`. |

### `fetch_webpage` Parameters

`fetch_webpage` is discoverable through `search_tools` in the default server listing.

The `fetch_webpage` tool supports chunked reading for large pages and optional proxy routing:

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `url` | string | required | HTTP/HTTPS URL to fetch |
| `max_length` | integer \| null | `null` | Maximum characters to return (chunk size) |
| `start_index` | integer | `0` | Character offset for pagination |
| `proxy_url` | string \| null | `null` | Optional HTTP(S) proxy URL for the request |

Notes:
- SSRF protection is always applied (private/internal hosts are blocked).
- `robots.txt` is checked before fetch when `protego` is installed.
- When output is truncated, the response includes a continuation hint with next `start_index`.
- If `proxy_url` is omitted, the server falls back to `FETCH_PROXY_URL` when set.
- `proxy_url` must be a public HTTP(S) host (private/internal proxy hosts are blocked).

Install the `web` extra for the highest-quality `fetch_webpage` experience:

```bash
pip install 'gemini-research-mcp[web]'
# or
uv add 'gemini-research-mcp[web]'
```

Without `[web]`, `fetch_webpage` still works using the built-in HTML fallback, but `trafilatura`
extraction and `protego`-based `robots.txt` checks are unavailable.

### Power User Workflow

[![Power User Workflow](https://raw.githubusercontent.com/MachineMates-AI/gemini-research-mcp/main/docs/workflow.svg)](docs/workflow.svg)

> **Key insight**: Gemini Deep Research runs asynchronously on Google's servers. Even if VS Code disconnects, your research continues. The `resume_research` tool retrieves completed work.

### Features

- **Auto-Clarification**: `research_deep` asks clarifying questions for vague queries. On the modern sessionless MCP protocol this uses a stateless guard pattern (`InputRequiredResult`, two independent tool calls, no server-held connection); legacy handshake clients still use [MCP Elicitation](https://modelcontextprotocol.io/specification/2025-11-25/client/elicitation) (`ctx.elicit()`)
- **Deep Research Max**: `research_deep_max` exposes Google's Max agent for exhaustive, high-stakes, and offline research workflows
- **Collaborative Planning**: `research_deep(..., collaborative_planning=True)` returns the drafted plan for approval before running the full report; refine or approve it with `refine_research_plan`
- **Visualization**: `visualization="auto"` lets Deep Research produce supporting images, persisted as downloadable MCP resource artifacts
- **MCP Tasks**: [Real-time progress](https://modelcontextprotocol.io/specification/2025-11-25/basic/utilities/tasks) with streaming updates
- **Session Persistence**: Research sessions are automatically saved and can be resumed later; shareable across instances with Redis (see [Storage backends](#storage-backends))
- **Persistent, Disk-First Exports**: Export to Markdown, JSON, or professional DOCX with Table of Contents; artifacts survive restarts and can be shared through Redis while files are still written to disk by default
- **File Search**: Search your own data alongside web using `file_search_store_names`
- **Remote MCP sources**: `research_deep_max` can call remote MCP servers using `mcp_servers`
- **Format Instructions**: Control report structure (sections, tables, tone)
- **LangChain-ready**: verified consumable via `langchain.mcp.MCPAdapter` (LangChain `1.4.0a2`) over both stdio and streamable-http - see [`scripts/langchain_interop_smoke.py`](scripts/langchain_interop_smoke.py). LangChain is never a dependency of this package.

## Installation

### PyPI (recommended)

```bash
pip install gemini-research-mcp
# or
uv add gemini-research-mcp
```

### Claude Desktop (MCPB Bundle)

Download the `.mcpb` bundle from [GitHub Releases](https://github.com/machinemates-ai/gemini-research-mcp/releases) and open it in Claude Desktop for single-click installation.

The bundle uses UV runtime - dependencies are installed automatically, no Python required.

## Configuration

| Variable | Required | Default | Description |
|----------|----------|---------|--------------|
| `GEMINI_API_KEY` | **Yes** | — | [Google AI Studio API key](https://aistudio.google.com/apikey) |
| `GEMINI_MODEL` | No | `gemini-3.7-flash` | Model for `research_web` |
| `GEMINI_SUMMARY_MODEL` | No | `gemini-3.7-flash` | Model for session summaries, titles, and clarification (thinking level `low`) |
| `DEEP_RESEARCH_AGENT` | No | `deep-research-preview-04-2026` | Default agent for `research_deep`; accepts `fast`, `standard`, `deep-research`, `max`, `deep-research-max`, or exact agent IDs |
| `FETCH_PROXY_URL` | No | — | Default HTTP(S) proxy for `fetch_webpage` |
| `GEMINI_RESEARCH_STORAGE_URL` | No | — | `redis://...` URL to share sessions/exports across multiple server instances/workers. Falls back to a local `DiskStore` when unset (see [Storage backends](#storage-backends)) |
| `GEMINI_RESEARCH_STORAGE_PATH` | No | XDG data dir | Custom directory for the local `DiskStore` |
| `GEMINI_RESEARCH_TTL_SECONDS` | No | backend default | Override session/export TTL |
| `GEMINI_RESEARCH_EXPORT_DIR` | No | `~/.gemini-research/exports/` | Disk-first destination when `export_research_session` has no `output_path` |
| `GEMINI_RESEARCH_TRANSPORT` | No | `stdio` | `stdio` (default, historical) or `streamable-http` (opt-in, see [Transports](#transports)) |
| `GEMINI_RESEARCH_HTTP_HOST` | No | `127.0.0.1` | Bind host for `streamable-http`. Non-loopback requires `GEMINI_RESEARCH_HTTP_BEARER_TOKEN` |
| `GEMINI_RESEARCH_HTTP_PORT` | No | `8000` | Bind port for `streamable-http` |
| `GEMINI_RESEARCH_HTTP_PATH` | No | `/mcp` | URL path for `streamable-http` |
| `GEMINI_RESEARCH_HTTP_BEARER_TOKEN` | No | — | Static bearer token required to call `streamable-http`. Never reuse `GEMINI_API_KEY` for this |

```bash
cp .env.example .env
# Edit .env with your API key
```

## Transports

The server defaults to **stdio**, matching every existing VS Code/Claude
Desktop configuration - no changes required for local, single-client use.

**Streamable HTTP** is opt-in, for remote or multi-client/multi-worker
deployments, and is sessionless (no sticky session required across calls):

```bash
# Local-only (no auth required, loopback binding):
uv run gemini-research-mcp --transport streamable-http

# Remote-accessible (bearer token required - refuses to start otherwise):
GEMINI_RESEARCH_HTTP_BEARER_TOKEN=$(openssl rand -hex 32) \
  uv run gemini-research-mcp --transport streamable-http --host 0.0.0.0 --port 8000
```

Binding to any non-loopback host (`0.0.0.0`, `::`, a LAN/public IP, etc.)
without `GEMINI_RESEARCH_HTTP_BEARER_TOKEN` set causes the server to refuse to
start - this prevents accidentally exposing your Gemini API quota to the
public internet. `127.0.0.1`/`localhost`/`::1` never require a token.

`--transport`, `--host`, `--port`, and `--path` CLI flags mirror the
`GEMINI_RESEARCH_TRANSPORT`/`GEMINI_RESEARCH_HTTP_HOST`/`GEMINI_RESEARCH_HTTP_PORT`/`GEMINI_RESEARCH_HTTP_PATH`
environment variables (CLI flags take precedence).

## Storage backends

Research sessions and export artifacts are stored through a single
backend-agnostic layer:

- **Local (default)**: a `DiskStore` under the XDG data directory
  (`GEMINI_RESEARCH_STORAGE_PATH` to override) - zero configuration, single
  process/single machine.
- **Distributed (Redis/Valkey)**: set `GEMINI_RESEARCH_STORAGE_URL=redis://host:6379/0`
  to share sessions and exports across multiple server instances or workers -
  a session created (or an export produced) on one instance is immediately
  readable from another. Requires the `distributed` extra:

```bash
uv add 'gemini-research-mcp[distributed]'
```



### Deep Research vs Deep Research Max

Google exposes Deep Research variants through the Gemini Interactions API `agent`
field, not the regular Gemini `model` field:

- `research_deep` uses `deep-research-preview-04-2026` by default. Use it for
  interactive research, comparisons, investigations, and latency/cost-sensitive
  synthesis.
- `research_deep_max` uses `deep-research-max-preview-04-2026`. Use it when the
  user explicitly asks for Max, exhaustive/comprehensive due diligence, market
  maps, literature reviews, board-ready reports, offline/nightly research, or
  maximum completeness over speed.

For Copilot and other LLM clients, the two tools are intentionally separate so
Max can be selected from the tool name and description. There is no public
`model` parameter for Deep Research, because follow-up and quick research use
Gemini models while Deep Research uses Interactions agents.

### Remote MCP servers for Deep Research

Google Deep Research exposes remote MCP server wiring through the Interactions
API. In this package, pass `mcp_servers` to `research_deep_max` when the agent
needs a specialized/private data source.

> **Experimental:** remote MCP is gated to
> `deep-research-max-preview-04-2026`. The standard
> `deep-research-preview-04-2026` agent has reproduced provider-side
> finalization/retrieval `500 api_error` failures after successful MCP tool
> calls; use `research_deep_max` or set
> `DEEP_RESEARCH_AGENT=deep-research-max-preview-04-2026`. See
> <https://github.com/googleapis/python-genai/issues/2126>.
>
> **Known limitation (live-verified):** even on `research_deep_max`, the
> provider-side agent may call the remote MCP tool successfully (confirmed via
> server-side access logs) yet fail to ground its final report in the
> returned data — paraphrasing a marker token instead of quoting it verbatim,
> or omitting specific evidence IDs/facts from a retrieved evidence ledger.
> This is preview-API agent behavior, not a bug in this package. Treat
> `research_deep_max` MCP evidence as best-effort: always verify citations
> against your own audit/quarantine path before trusting a report for
> decisions.

Example `research_deep_max` `mcp_servers` argument:

```json
{
  "query": "Use the Market Researcher MCP evidence ledger to analyze the approved market gate.",
  "mcp_servers": [
    {
      "name": "Market Researcher MCP",
      "url": "https://example.com/mcp",
      "headers": {
        "Authorization": "Bearer ${TOKEN}"
      },
      "allowed_tools": [
        "market_get_mission",
        "market_get_runtime_policy",
        "market_get_task_status",
        "market_generate_report"
      ]
    }
  ]
}
```

Use `allowed_tools` aggressively. For evidence-led workflows, expose read-only
ledger/report/status tools to Deep Research Max and import the resulting report back
through your own audit/quarantine path. The MCP server tool accepts the
user-friendly string list shown above and normalizes it to the Gemini
Interactions API `allowed_tools` object shape before sending the request.

If Gemini returns a generic `400 invalid_request` before the research task
starts, use `inspect_mcp_server_for_gemini` first. It lists the remote MCP
server tools and flags common compatibility problems such as missing tool
descriptions, empty input schemas, unsupported JSON Schema keywords, or
`allowed_tools` names that do not exist on the server. Public quick-tunnel hosts
may still be rejected before Gemini contacts the server; prefer a stable HTTPS
deployment for production E2E tests.

Live E2E validation is intentionally skipped by default because it is paid,
slow, and depends on preview APIs. There are two useful levels:

1. Minimal marker smoke test: proves remote MCP result inclusion with a stable
   HTTPS MCP fixture that returns `MCP_E2E_FIXTURE_7B9F2A` from
   `get_guardrail_summary`.

```bash
GEMINI_API_KEY=... \
GEMINI_MCP_E2E_URL=https://fresh-stable-fixture.example/mcp \
uv run pytest -m e2e tests/test_deep_research_max_mcp_e2e.py -q
```

2. Realistic evidence-inclusion test: proves Deep Research Max can start a new
   research task and integrate substantive MCP-only evidence into the final
   report. The fixture should expose read-only tools such as
   `market_get_mission`, `market_get_evidence_ledger`,
   `market_get_runtime_policy`, and `market_generate_report`.

```bash
GEMINI_API_KEY=... \
GEMINI_MCP_REALISTIC_E2E_URL=https://fresh-realistic-fixture.example/mcp \
GEMINI_MCP_E2E_ARTIFACT_DIR=/tmp/gemini-realistic-e2e \
uv run pytest -m e2e tests/test_deep_research_max_mcp_e2e.py \
  -q -s -k realistic_evidence_inclusion
```

The realistic test checks for multiple MCP-only evidence IDs, distinctive
metrics, platform constraints, a derived gate recommendation, and absence of the
hidden/disallowed tool canary.

## Usage

### VS Code MCP

Add to `.vscode/mcp.json`:

```json
{
  "servers": {
    "gemini-research": {
      "command": "uvx",
      "args": ["gemini-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}
```

Or run from source:

```json
{
  "servers": {
    "gemini-research": {
      "command": "uv",
      "args": ["run", "--directory", "path/to/gemini-research-mcp", "gemini-research-mcp"],
      "envFile": "${workspaceFolder}/path/to/gemini-research-mcp/.env"
    }
  }
}
```

### Command Line

```bash
uv run gemini-research-mcp
# or
uvx gemini-research-mcp
```

## DOCX Export

Export research sessions to professional Word documents with:

- **Cover page** with title, date, and research metadata
- **Clickable Table of Contents** with navigation to sections
- **Professional typography**: Calibri fonts, 1-inch margins, 1.5x line spacing
- **Executive summary** with elegant formatting
- **Full research report** with proper heading hierarchy
- **Sources section** with full clickable URLs
- **Metadata table** with session details

### VS Code Setup

To enable DOCX export, install with the `[docx]` extra:

```json
{
  "servers": {
    "gemini-research": {
      "command": "uvx",
      "args": ["--from", "gemini-research-mcp[docx]", "gemini-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}
```

### Downloading Files

`export_research_session` is **disk-first**: the file is always written
to disk and the absolute path is returned on the first line of the
response text (e.g. `✅ **Saved to:** /…/report.docx`). This means any
MCP client — GUI or headless — gets a usable file path back.

By default exports are written to `GEMINI_RESEARCH_EXPORT_DIR`
(defaults to `~/.gemini-research/exports/`; falls back to the system
temp dir if that location isn't writable). Override per-call with the
`output_path` argument:

```jsonc
{
  "name": "export_research_session",
  "arguments": {
    "interaction_id": "v1_...",
    "format": "docx",
    "output_path": "/absolute/or/relative/path/report.docx"
  }
}
```

When `output_path` is supplied, the parent directory must already
exist (no silent `mkdir`). GUI hosts (e.g. VS Code Copilot Chat) also
receive an `EmbeddedResource` attachment backed by the persistent
`research://exports/{id}` resource store for native "Save As" — clients that can't render it can safely ignore it.

### Client compatibility

`research_deep` requires [MCP Tasks support](https://modelcontextprotocol.io/specification/2025-11-25/basic/utilities/tasks)
(SEP-1732) on the client. Clients that do not advertise the `tasks`
capability will receive a `-32600` error.

Known client status:

- **VS Code Copilot Chat / MCP Inspector / Claude Desktop** — supported.
- **GitHub Copilot CLI** — tracked upstream at
  [github/copilot-cli#2538](https://github.com/github/copilot-cli/issues/2538);
  until that lands, use `research_web` from the CLI.

### Installation (pip/uv)

```bash
# Install with DOCX support
pip install 'gemini-research-mcp[docx]'
# or
uv add 'gemini-research-mcp[docx]'
```

### Features

| Feature | Description |
|---------|-------------|
| **Cover Page** | Title, date, duration, tokens, AI agent |
| **Clickable TOC** | Internal hyperlinks navigate to sections |
| **Syntax Highlighting** | Pygments-powered code blocks with GitHub colors |
| **Professional Styling** | Calibri fonts, proper heading hierarchy (H1-H4) |
| **Page Margins** | Standard 1-inch (2.54cm) margins |
| **Heading Spacing** | `keep_with_next` prevents orphan headings |
| **Sources** | Full URLs as clickable hyperlinks |
| **Pure Python** | No external binaries (Pandoc not required) |

## Resources

MCP Resources provide read-only data that clients can access:

| Resource | Description |
|----------|-------------|
| `research://models` | Available models and their capabilities |
| `research://exports` | List cached exports ready for download |
| `research://exports/{id}` | Download an exported file (Markdown, JSON, or DOCX) |

### File Downloads

The `export_research_session` tool creates exports and returns a resource URI. Clients (like VS Code) can then fetch the resource to download the file with proper MIME type handling.

## Development

```bash
uv sync --extra dev
uv run pytest
uv run mypy src/
uv run ruff check src/
```

### Tests

```bash
uv run pytest                    # Unit tests
uv run pytest -m e2e             # E2E tests (requires GEMINI_API_KEY)
uv run pytest --cov=src/gemini_research_mcp  # With coverage
```

## Pricing

| Tool | Typical Cost |
|------|-------------|
| `research_web` | ~$0.01-0.05 per query |
| `research_deep` | ~$2-5 per task |

*Deep Research uses ~80-160 searches and ~250k-900k tokens per task.*

## License

MIT
