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    Smithery Openapi Server

    OpenAPI server for Smithery Registry, providing access to MCP servers

    0 stars
    Python
    Updated Apr 5, 2025

    Table of Contents

    • Features
    • Authentication
    • Usage
    • Installation
    • Running the server
    • API Endpoints
    • WebSocket Connection
    • Integration with OpenAPI Tools
    • TypeScript SDK Usage
    • License

    Table of Contents

    • Features
    • Authentication
    • Usage
    • Installation
    • Running the server
    • API Endpoints
    • WebSocket Connection
    • Integration with OpenAPI Tools
    • TypeScript SDK Usage
    • License

    Documentation

    Smithery Registry OpenAPI Server

    This server provides an OpenAPI interface to the Smithery Registry API, allowing you to search and obtain launch configurations for Model Context Protocol (MCP) servers.

    Features

    • List available MCP servers with advanced filtering
    • Get detailed server information including connection configurations
    • Generate WebSocket URLs with base64-encoded configurations
    • Authentication via bearer token
    • Compatible with OpenAPI tools and clients

    Authentication

    All requests to the Smithery Registry API require authentication:

    • You need a bearer token in the Authorization header
    • Format: Authorization: Bearer your-api-token
    • Obtain a token from your Smithery user profile under API keys

    Usage

    Installation

    bash
    pip install -r requirements.txt

    Running the server

    bash
    uvicorn main:app --host 0.0.0.0 --port 8000 --reload

    API Endpoints

    1. GET /servers - List available MCP servers

    • Query parameters:
    • q: Search query (semantic search)
    • page: Page number (default: 1)
    • pageSize: Items per page (default: 10)
    • Advanced filtering syntax in the q parameter:
    • Text search: "machine learning"
    • Owner filter: owner:username
    • Repository filter: repo:repository-name
    • Deployment status: is:deployed
    • Example: "owner:smithery-ai repo:fetch is:deployed machine learning"

    2. GET /servers/{qualified_name} - Get detailed information about a specific server

    3. POST /create-websocket-url - Create a WebSocket URL with encoded config

    • Request body:
    json
    {
           "qualifiedName": "username/repository",
           "config": {
             // Configuration object matching the server's schema
           }
         }

    WebSocket Connection

    For direct WebSocket connections to MCP servers:

    • URL Format: https://server.smithery.ai/${qualifiedName}/ws?config=${base64encode(config)}
    • Config must comply with the server's configSchema
    • Config is base64-encoded JSON

    Integration with OpenAPI Tools

    This server is designed to be compatible with any OpenAPI-compliant tools and frameworks. The API follows RESTful conventions and provides detailed OpenAPI documentation at the /docs endpoint when running.

    TypeScript SDK Usage

    For use with the Smithery TypeScript SDK:

    typescript
    import { WebSocketClientTransport } from "@modelcontextprotocol/sdk/client/websocket.js"
    import { createSmitheryUrl } from "@smithery/sdk/config.js"
    
    const url = createSmitheryUrl(
      "https://your-smithery-mcp-server/ws",
      {
        // config object matching schema
      },
    )
    const transport = new WebSocketClientTransport(url)

    License

    MIT

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