fast-mcp
by Manas-maker
README.md
# fast-mcp
<!-- mcp-name: io.github.Manas-maker/fast-mcp -->
> **FastAPI-native Model Context Protocol (MCP) framework** with automatic route reflection, ASGI scope bridging, dynamic progressive tool discovery, resilient error recovery, and interactive in-chat MCP Apps (SEP-1865).
[](https://pypi.org/project/mcp-fastapi/)
[]()
[](https://manas-maker.github.io/fast-mcp/)
[]()
[]()
[](https://glama.ai/mcp/servers/Manas-maker/fast-mcp)
---
## Highlights
- β‘ **Hybrid Dual-Citizen ASGI Mount:** Mounts directly onto any existing `FastAPI` instance in-process over standard ASGIβzero external proxying, zero hanging subprocesses.
- π **Local stdio CLI Runner & Desktop AI Bridge:** Run `fast-mcp stdio main:app` or `python -m fast_mcp stdio main:app` to connect desktop AI clients (Claude Desktop, Cursor) over standard I/O pipes with zero network setup.
- π **Route Reflection:** Opt-in tags (`tags=["mcp"]`) automatically convert FastAPI endpoints, Pydantic models, docstrings, path/query/body parameters into MCP tools.
- π οΈ **Custom AI Tools (`@mcp.tool`):** Define AI-tailored composite tools alongside reflected routes with automatic schema and docstring extraction.
- π **ASGI Scope Bridging:** Client authorization headers (`Authorization: Bearer <token>`, cookies, API keys) captured during the MCP handshake are bridged into an in-memory ASGI `Request`, natively resolving FastAPI's `Depends()` and `Security()` providers without code changes.
- π§ **Dynamic Progressive Tool Discovery:** Protect agent context windows via progressive discovery (`dynamic_discovery=True`), the `search_tools(query: str)` meta-tool, and zero-dependency `KeywordTagRouter`.
- π‘οΈ **Resilient Error Recovery & Minified JSON:** Traps route `HTTPException` and Pydantic validation errors into informative `CallToolResult(isError=True)` responses so LLMs can self-correct without protocol failures. Output defaults to compact, token-conscious minified JSON with custom `@mcp.serializer` formatting hooks.
- π₯οΈ **Dual UI & In-Chat MCP Apps (SEP-1865):** Embedded browser inspector at `/mcp/docs` plus native support for in-chat interactive iframes in desktop AI clients (Claude Desktop, Cursor, VS Code) via `_meta.ui.resourceUri`, the built-in `inspect()` tool, and the `@mcp.app()` decorator.
---
## Installation
```bash
pip install mcp-fastapi
```
Or using `uv`:
```bash
uv add mcp-fastapi
```
---
## Quickstart
```python
from fastapi import FastAPI, Depends, Header, HTTPException
from pydantic import BaseModel, Field
from fast_mcp import FastMCP
app = FastAPI(title="Store API")
mcp = FastMCP(app=app, name="store-mcp")
# 1. Existing FastAPI route reflected automatically via tags=["mcp"]
class Product(BaseModel):
id: int
name: str
price: float
@app.get("/products/{product_id}", tags=["mcp"])
async def get_product(product_id: int) -> Product:
"""Fetch product details by ID."""
if product_id == 404:
raise HTTPException(status_code=404, detail="Product not found")
return Product(id=product_id, name="Smart Widget", price=29.99)
# 2. Custom AI tool with native dependency injection
def verify_token(authorization: str = Header(...)) -> str:
if not authorization.startswith("Bearer "):
raise HTTPException(status_code=401, detail="Invalid token")
return authorization.split(" ")[1]
@mcp.tool(name="order_status", description="Check customer order status")
def check_order(order_id: str, user: str = Depends(verify_token)) -> dict:
return {"order_id": order_id, "customer": user, "status": "Shipped"}
# 3. Mount MCP endpoints (/mcp/sse, /mcp/messages, /mcp/docs)
mcp.mount()
```
Run with standard ASGI servers:
```bash
uvicorn main:app --reload
```
---
## Core Capabilities
### 1. Route Reflection
Routes tagged with `tags=["mcp"]` (configurable via `route_tag`) are automatically inspected upon `mcp.mount()`:
- Endpoint docstrings (Google, Sphinx, NumPy format) become tool descriptions and parameter docs.
- Pydantic request models, query parameters, and path variables become MCP input schemas.
- Untagged endpoints remain standard HTTP routes and are never leaked to LLMs.
```python
@app.post("/items/create", tags=["mcp"])
async def create_item(item: ItemModel) -> ItemModel:
"""Create a new catalog item.
Args:
item: The catalog item specification.
"""
return item
```
### 2. Custom AI Tools (`@mcp.tool`)
Register AI-specialized tools that don't need dedicated REST endpoints:
```python
# Bare decorator
@mcp.tool
def calculate_quote(quantity: int, discount: float = 0.0) -> float:
return quantity * 100.0 * (1.0 - discount)
# Parameterized decorator
@mcp.tool(name="inventory_lookup", description="Lookup stock levels", tags=["inventory"])
async def check_inventory(sku: str) -> dict:
return {"sku": sku, "in_stock": True, "count": 42}
```
### 3. ASGI Scope Bridging & Native Auth
Incoming headers (`Authorization: Bearer ...`, cookies, API keys) from the MCP client's SSE handshake or message posts are captured into an active request context:
```python
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
security = HTTPBearer()
@mcp.tool
async def user_profile(creds: HTTPAuthorizationCredentials = Depends(security)) -> dict:
token = creds.credentials
return {"user": "alice", "token_verified": True}
```
If authorization fails or headers are omitted, `fast-mcp` unwraps the resulting `HTTPException(401)` into `CallToolResult(is_error=True)` so the agent receives an actionable authentication error rather than crashing the transport.
### 4. Dynamic Progressive Tool Discovery
Prevent LLM context window bloat on large FastAPI applications with hundreds of endpoints:
```python
mcp = FastMCP(
app=app,
dynamic_discovery=True, # Or set dynamic_discovery_threshold=20
baseline_tools=["search_tools", "get_system_status"],
baseline_tag="baseline",
)
```
- When active, `tools/list` exposes only baseline tools plus the `search_tools(query: str)` meta-tool.
- Calling `search_tools(query="invoice")` executes the pluggable `ToolRouter` (defaults to zero-dependency `KeywordTagRouter` with tokenized name/tag/description ranking) and returns matching tool definitions with full JSON schemas.
### 5. Resilient Error Interception & Custom Serializers
- **Exception Traps:** `HTTPException` (400, 404, 422) and Pydantic validation errors return clean, concise messages with `isError=True`.
- **Minified Output:** Responses serialize to compact minified JSON (`{"id":1,"name":"widget"}`) saving prompt tokens.
- **Custom Serializers:** Format return types into tailored markdown or summaries:
```python
class Report(BaseModel):
title: str
metrics: dict[str, int]
@mcp.serializer(Report)
def format_report(report: Report) -> str:
md = f"### {report.title}\n"
for k, v in report.metrics.items():
md += f"- **{k}**: {v}\n"
return md
```
### 6. Dual UI: Browser Inspector & In-Chat MCP Apps (SEP-1865)
#### Embedded Browser Inspector
Open `http://localhost:8000/mcp/docs` in any browser to inspect registered tools, view schemas, and execute test invocations interactively without external Node.js CLIs. (Disable with `FastMCP(app, enable_ui=False)`).
#### In-Chat MCP Apps (SEP-1865)
Render rich interactive HTML/JS widgets directly in modern desktop AI clients (Claude Desktop, Cursor, VS Code):
```python
# Built-in server inspector tool
# Agent calling `inspect()` receives an interactive iframe pointed to ui://fast-mcp/inspector
# Authoring custom in-chat widgets:
@mcp.app(
name="dashboard",
resource_uri="ui://store/dashboard",
html="""
<div style="font-family: sans-serif; padding: 1rem; border-radius: 8px; background: #f0f4f8;">
<h2>Store Live Metrics</h2>
<p>Active Users: <strong>1,420</strong></p>
</div>
"""
)
def live_dashboard() -> str:
return '<iframe src="ui://store/dashboard" width="100%" height="400"></iframe>'
```
### 7. Local stdio CLI Runner & Desktop AI Bridge
Connect desktop AI clients (Claude Desktop, Cursor) directly to your FastAPI backend or FastMCP instance over standard input/output (`stdio`) pipes with zero network setup, port conflicts, or external proxying.
#### Command-Line Usage
```bash
# Run stdio runner pointing to FastAPI app or FastMCP instance
fast-mcp stdio main:app
# Or via Python module invocation
python -m fast_mcp stdio main:app
# Target attribute defaults to 'app' or 'mcp' if omitted:
fast-mcp stdio main
# The 'stdio' subcommand can also be omitted as default:
fast-mcp main:app
```
#### Claude Desktop Configuration (`claude_desktop_config.json`)
Configure Claude Desktop to launch your FastMCP server directly:
```json
{
"mcpServers": {
"my-fast-mcp-app": {
"command": "fast-mcp",
"args": ["stdio", "main:app"]
}
}
}
```
Or using `uv` to manage the virtual environment automatically:
```json
{
"mcpServers": {
"my-fast-mcp-app": {
"command": "uv",
"args": ["run", "fast-mcp", "stdio", "main:app"]
}
}
}
```
#### Programmatic Stdio Runner
You can also run stdio mode programmatically from Python:
```python
import asyncio
from fast_mcp import FastMCP, run_stdio
mcp = FastMCP(name="my-stdio-server")
@mcp.tool()
def add(a: int, b: int) -> int:
return a + b
if __name__ == "__main__":
asyncio.run(run_stdio(mcp))
```
---
## Testing & Verification
`fast-mcp` exercises external behavior across the **ASGI Protocol Seam** using `httpx.AsyncClient` with `ASGITransport`:
```bash
# Run full test suite
pytest
# Run tests with coverage
pytest --cov=fast_mcp --cov-report=term-missing
```
---
## Specification & Architectural Documents
- [Interactive Documentation Website](https://manas-maker.github.io/fast-mcp/)
- [AI Agent Index (llms.txt)](https://manas-maker.github.io/fast-mcp/llms.txt)
- [Specification: fast-mcp Core Framework (V1)](docs/specs/0001-fast-mcp-core.md)
- [GLOSSARY.md](GLOSSARY.md)
- [ADR 0001: Architecture Foundation and Hybrid Scope](docs/adr/0001-architecture-foundation.md)
- [ADR 0002: Dual-UI, ASGI Scope Bridging, and Resilient Error Handling](docs/adr/0002-dual-ui-auth-bridging-and-error-handling.md)
---
## License
MIT
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