Metadata-Version: 2.4
Name: trishul-mcp
Version: 0.1.0
Summary: Trishul: Deterministic repository-scale code intelligence Model Context Protocol (MCP) server.
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: mcp>=1.0.0
Requires-Dist: httpx>=0.25.0
Requires-Dist: pydantic>=2.0.0

# trishul-mcp

Deterministic, repository-scale semantic code intelligence Model Context Protocol (MCP) server for AI coding agents (Claude Code, Cursor, Windsurf).

## Overview

`trishul-mcp` connects AI coding assistants directly to a persistent, topological code intelligence graph. Instead of burning your model's context window re-reading thousands of raw files or guessing caller hierarchies with naive regex, Trishul provides deterministic answers with verified certainty:

- **Callers (`get_callers`)**: Who directly or indirectly invokes a symbol?
- **Blast Radius (`get_blast` / `get_impact`)**: What breaks upstream if this function or interface changes?
- **Execution Paths (`get_path`)**: What is the optimal, deterministic call path between Symbol A and Symbol B?
- **Dependency Hubs (`get_dependency_hubs`)**: What are the critical architectural bottlenecks and chokepoints?

## Installation

```bash
pip install trishul-mcp
```
*(Or install via `pip install llmgraph-in`)*

## MCP Client Configuration

Add to your `claude_desktop_config.json`, Cursor MCP settings, or Windsurf configuration:

```json
{
  "mcpServers": {
    "trishul": {
      "command": "trishul-mcp",
      "env": {
        "TRISHUL_API_KEY": "llmg_live_...",
        "TRISHUL_API_URL": "https://api.llmgraph.in/v1"
      }
    }
  }
}
```

*Note: `LLMGRAPH_API_KEY` and `LLMGRAPH_API_URL` are also supported for backward compatibility.*

## License

Apache-2.0. Developed by Brainfoods Studio.
