litestar-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@litestar-mcplist all users"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Litestar MCP Plugin
A lightweight plugin that integrates Litestar web applications with the Model Context Protocol (MCP) by exposing marked routes as MCP tools, resources, and prompts over MCP Streamable HTTP and JSON-RPC.
Overview
This plugin automatically discovers Litestar routes marked for MCP and exposes them through an MCP-native transport surface. Pass mcp_tool="name", mcp_resource="name", or mcp_prompt="name" straight through to @get / @post / etc. — Litestar funnels unknown kwargs into handler.opt, so no second decorator or opt={...} wrapper is needed. Standalone prompt callables that are not bound to an HTTP route can be registered through LitestarMCP(prompts=[...]).
Related MCP server: backend2mcp
Features
Protocol-Native Transport — MCP Streamable HTTP with JSON-RPC requests and SSE streams.
Three MCP Primitives — tools, resources, and prompts, with
prompts/listandprompts/getdriven by the same handler discovery as the rest of the surface.Simple Route Marking — pass
mcp_tool/mcp_resource/mcp_promptkwargs straight through to Litestar's route decorators, or register standalone prompts viaLitestarMCP(prompts=[...]).RFC 6570 URI Templates —
mcp_resource_template="app://…/{var}"dispatches concrete URIs to handlers with extracted vars.First-Class Descriptions — structured
mcp_description,mcp_agent_instructions,mcp_when_to_use,mcp_returnskwargs.Type Safe — full type hints with dataclasses;
msgspec-powered tool-argument validation.Automatic Discovery — routes are discovered at app initialization.
OpenAPI Integration — server info derived from OpenAPI config.
OIDC Auth Baked In — bearer-token validation via
MCPAuthBackendor a composablecreate_oidc_validator()factory; injectableJWKSCacheprotocol for shared document caches.Optional Task Support — experimental in-memory MCP task lifecycle endpoints.
Quick Start
Installation
pip install litestar-mcp
# or
uv add litestar-mcpBasic Usage
from litestar import Litestar, get, post
from litestar.openapi.config import OpenAPIConfig
from litestar_mcp import LitestarMCP
# Mark routes for MCP exposure using the opt attribute
@get("/users", mcp_tool="list_users")
async def get_users() -> list[dict]:
"""List all users in the system."""
return [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]
@post("/analyze", mcp_tool="analyze_data")
async def analyze_data(data: dict) -> dict:
"""Analyze the provided data and return insights."""
return {"result": f"Analyzed {len(data)} items"}
@get("/config", mcp_resource="app_config")
async def get_app_config() -> dict:
"""Get the current application configuration."""
return {"debug": True, "version": "1.0.0"}
# Add the MCP plugin to your Litestar app
app = Litestar(
route_handlers=[get_users, analyze_data, get_app_config],
plugins=[LitestarMCP()],
openapi_config=OpenAPIConfig(title="My API", version="1.0.0"),
)Standalone Application (Alternative)
If you are building a standalone MCP server, you can use the MCP class which provides a simplified declarative API and programmatically boots the server using the standard Litestar CLI:
from litestar_mcp import MCP
# 1. Initialize the application
mcp = MCP("my-mcp-server", instructions="Exposes utility tools.")
# 2. Register tools, resources, or prompts using decorators
@mcp.tool()
def add(a: int, b: int) -> int:
"""Calculate the sum of two integers."""
return a + b
# 3. Expose the app globally so that the CLI can discover it
app = mcp.app
if __name__ == "__main__":
# 4. Boot the server using Server-Sent Events (SSE)
mcp.run(port=8000)The standalone decorators accept Litestar route-handler keyword arguments such as dependencies, guards, response_headers, responses, summary, tags, DTO options, hooks, and arbitrary extra kwargs stored in handler.opt. The name keyword names the MCP primitive; use route_name to set Litestar's route-handler name separately.
With Configuration
from litestar_mcp import LitestarMCP, MCPConfig
config = MCPConfig(
base_path="/api/mcp", # Change the base path
name="Custom Server Name", # Override server name
include_in_schema=True, # Include MCP routes in OpenAPI schema
)
app = Litestar(
route_handlers=[get_users, analyze_data, get_app_config],
plugins=[LitestarMCP(config)],
openapi_config=OpenAPIConfig(title="My API", version="1.0.0"),
)Resources vs Tools: When to Use Each
Use Resources (mcp_resource) for
Read-only data that AI models need to reference
Static or semi-static information like documentation, schemas, configurations
Data that doesn't require parameters to retrieve
Reference material that AI models should "know about"
Examples:
@get("/schema", mcp_resource="database_schema")
async def get_schema() -> dict:
"""Database schema information."""
return {"tables": ["users", "orders"], "relationships": [...]}
@get("/docs", mcp_resource="api_docs")
async def get_documentation() -> dict:
"""API documentation and usage examples."""
return {"endpoints": [...], "examples": [...]}Use Tools (mcp_tool) for
Actions that perform operations or mutations
Dynamic queries that need input parameters
Operations that change state in your application
Computations or data processing tasks
Examples:
@post("/users", mcp_tool="create_user")
async def create_user(user_data: dict) -> dict:
"""Create a new user account."""
# Perform user creation logic
return {"id": 123, "created": True}
@get("/search", mcp_tool="search_data")
async def search(query: str, limit: int = 10) -> dict:
"""Search through application data."""
# Perform search with parameters
return {"results": [...], "total": 42}How It Works
Route Discovery: At app initialization, the plugin scans all route handlers for the
optattributeAutomatic Exposure: Routes marked with
mcp_toolormcp_resourceare automatically exposedMCP Transport: The plugin adds a Streamable HTTP MCP endpoint under the configured base path (default
/mcp)Server Info: Server name and version are derived from your OpenAPI configuration
MCP Endpoints
Once configured, your application exposes these MCP-compatible endpoints:
POST /mcp- stateless MCP2026-07-28JSON-RPC and subscription streamsGET /.well-known/agent-card.json- Agent metadata cardGET /.well-known/oauth-protected-resource- OAuth protected resource metadata when auth is configured
Use server/discover instead of an initialize handshake:
curl -X POST http://127.0.0.1:8000/mcp \
-H 'Content-Type: application/json' \
-H 'MCP-Protocol-Version: 2026-07-28' \
-H 'Mcp-Method: server/discover' \
-d '{"jsonrpc":"2.0","id":1,"method":"server/discover","params":{"_meta":{"io.modelcontextprotocol/protocolVersion":"2026-07-28","io.modelcontextprotocol/clientCapabilities":{},"io.modelcontextprotocol/clientInfo":{"name":"curl","version":"1"}}}}'Every request is independent. There are no protocol sessions, sticky-routing headers, GET/DELETE transport handlers, or SSE replay.
Built-in Resources:
litestar://openapi- Your application's OpenAPI schema (always available viaresources/read)
Configuration
Configure the plugin using MCPConfig:
from litestar_mcp import MCPConfig
config = MCPConfig()Configuration Options:
Option | Type | Default | Description |
|
|
| Base path for the MCP Streamable HTTP endpoint |
|
|
| Whether to include MCP routes in OpenAPI schema |
|
|
| Override server name. If None, uses OpenAPI title |
|
|
| Litestar guards applied to the MCP router |
|
|
| Exact additional Origins; present Origins must be same-origin or allowlisted |
|
|
| Only expose matching operation names |
|
|
| Exclude matching operation names |
|
|
| Only expose routes with matching OpenAPI tags |
|
|
| Exclude routes with matching OpenAPI tags |
|
|
| Metadata for |
|
|
| Enable the |
|
|
| Conservative cache lifetime for discovery/list/resource results |
|
|
| Cache sharing policy |
|
|
| Maximum concurrent |
|
|
| Subscription keepalive interval |
|
|
| Optional cross-worker notification fan-out |
|
|
| Observe each |
|
|
| Observe each |
Complete Example
from litestar import Litestar, get, post, delete
from litestar.openapi.config import OpenAPIConfig
from litestar_mcp import LitestarMCP, MCPConfig
# Resources - read-only reference data
@get("/users/schema", mcp_resource="user_schema")
async def get_user_schema() -> dict:
"""User data model schema."""
return {
"type": "object",
"properties": {
"id": {"type": "integer"},
"name": {"type": "string"},
"email": {"type": "string"}
}
}
@get("/api/info", mcp_resource="api_info")
async def get_api_info() -> dict:
"""API capabilities and information."""
return {
"version": "2.0.0",
"features": ["user_management", "data_analysis"],
"rate_limits": {"requests_per_minute": 1000}
}
# Tools - actionable operations
@get("/users", mcp_tool="list_users")
async def list_users(limit: int = 10) -> dict:
"""List users with optional limit."""
# Fetch users from database
return {"users": [{"id": 1, "name": "Alice"}], "total": 1}
@post("/users", mcp_tool="create_user")
async def create_user(user_data: dict) -> dict:
"""Create a new user account."""
# Create user logic
return {"id": 123, "created": True, "user": user_data}
@post("/analyze", mcp_tool="analyze_dataset")
async def analyze_dataset(config: dict) -> dict:
"""Analyze data with custom configuration."""
# Analysis logic
return {"insights": [...], "metrics": {...}}
# Regular routes (not exposed to MCP)
@get("/health")
async def health_check() -> dict:
return {"status": "healthy"}
# MCP configuration
mcp_config = MCPConfig(
name="User Management API",
base_path="/mcp"
)
# Create Litestar app
app = Litestar(
route_handlers=[
get_user_schema, get_api_info, # Resources
list_users, create_user, analyze_dataset, # Tools
health_check # Regular route
],
plugins=[LitestarMCP(mcp_config)],
openapi_config=OpenAPIConfig(
title="User Management API",
version="2.0.0"
),
)Authentication
Authentication is a Litestar middleware concern. Apps with an existing auth
middleware get MCP authentication for free — request.user and request.auth
are populated before tool handlers run. Three integration paths:
Path A — Bring Your Own Middleware
If your Litestar app already ships an AbstractAuthenticationMiddleware (or
Litestar's built-in JWT backends), MCP inherits it automatically:
from litestar import Litestar
from litestar.middleware import DefineMiddleware
from litestar_mcp import LitestarMCP, MCPConfig
app = Litestar(
route_handlers=[...],
plugins=[LitestarMCP(MCPConfig())],
middleware=[DefineMiddleware(YourAuthMiddleware)], # MCP gets this for free
)See docs/examples/notes/sqlspec/google_iap.py for a runnable example.
Path B — Built-in MCPAuthBackend
For OIDC workloads, install the built-in MCPAuthBackend:
from litestar import Litestar
from litestar.middleware import DefineMiddleware
from litestar_mcp import LitestarMCP, MCPAuthBackend, MCPConfig, OIDCProviderConfig
from litestar_mcp.auth import MCPAuthConfig
app = Litestar(
route_handlers=[...],
plugins=[LitestarMCP(MCPConfig(auth=MCPAuthConfig(
issuer="https://company.okta.com",
audience="api://mcp-tools",
)))],
middleware=[DefineMiddleware(
MCPAuthBackend,
providers=[OIDCProviderConfig(
issuer="https://company.okta.com",
audience="api://mcp-tools",
)],
user_resolver=lambda claims, app: MyUser(sub=claims["sub"]),
)],
)JWKS auto-discovery, caching, and clock_skew tolerance are built in.
See docs/examples/notes/sqlspec/cloud_run_jwt.py for the full pattern.
Path C — Composable OIDC Factory
create_oidc_validator() returns an async callable for use as
MCPAuthBackend(token_validator=...) or inside your own middleware:
from litestar_mcp import create_oidc_validator
validator = create_oidc_validator(
"https://cloud.google.com/iap",
"/projects/PROJECT_NUMBER/global/backendServices/SERVICE_ID",
algorithms=("ES256",),
jwks_cache_ttl=1800,
)Development
# Clone the repository
git clone https://github.com/litestar-org/litestar-mcp.git
cd litestar-mcp
# Install with development dependencies
make install
# Run the complete Python quality gate
make check-all
# Run the pinned MCP 2026-07-28 conformance suite
make conformance
# Build strict documentation and validate examples
make docs
make validate-examples validate-uvx validate-pep723
# Run example
uv run python docs/examples/hello_world/main.pyThe conformance target owns Node.js 24.18.1 through NODE_VERSION in the
Makefile. When nodenv is available, the
target selects that version with NODENV_VERSION; otherwise it uses the
active node/npm installation. A local .node-version is ignored so
contributors can use nodenv without changing repository state.
License
MIT License. See LICENSE for details.
Contributing
Contributions welcome! Please see our contribution guide for details.
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