MCP Advisor

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MCP Advisor & Installation

Experience MCP Advisor

What is this?

MCP Advisor is a discovery & recommendation service that helps you explore Model Context Protocol servers. It acts as a smart guide that helps AI assistants find and understand available MCP services out there based on natural language queries, making it easier to discover and utilize the right tools for specific tasks.

Features

• Smart Search: Find MCP services using natural language queries
• Rich Metadata: Get detailed information about each service
• Real-time Updates: Always up-to-date with the latest MCP services
• Easy Integration: Simple to integrate with any MCP-compatible AI assistant
• Vector Search: Powered by OceanBase for high-performance semantic search
• Modular Architecture: Clean separation of concerns for maintainability and extensibility

Architecture

graph TD
    Client[AI Assistant/Client] --> |Query| Server[MCP Advisor Server]
    Server --> |Request| SearchService[Search Service]
    SearchService --> |Query| Provider1[Compass Search Provider]
    SearchService --> |Query| Provider2[GetMCP Search Provider]
    Provider1 --> |API Call| ExternalAPI[External MCP Registry API]
    Provider2 --> |Fetch Data| GetMCPAPI[GetMCP API]
    Provider2 --> |Vector Search| OceanBase[OceanBase Vector DB]
    SearchService --> |Results| Server
    Server --> |Response| Client

    subgraph "MCP Advisor Core"
        Server
        SearchService
        Provider1
        Provider2
    end

    subgraph "Data Layer"
        GetMCPAPI
        OceanBase
        ExternalAPI
    end

    subgraph "Transport Options"
        Stdio[Stdio Transport]
        SSE[SSE Transport]
        REST[REST Transport]
    end

    Server --> Stdio
    Server --> SSE
    Server --> REST

Data Flow

sequenceDiagram
    participant Client as AI Assistant
    participant Service as SearchService
    participant Provider as GetMcpSearchProvider
    participant DB as OceanBase

    Client->>Service: Query Request
    Service->>Provider: search(query)
    
    Provider->>Provider: Generate Query Embedding
    Provider->>DB: Vector Similarity Search
    DB-->>Provider: Return Similar Servers
    Provider-->>Service: Return Formatted Results
    Service-->>Client: Return Combined Results

Quick Start

Usage

1. Clone the repository

or

2. Use npx

Installation

For Claude Desktop, edit your claude_desktop_config.json file:

MacOS/Linux

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

code $env:AppData\Claude\claude_desktop_config.json

Transport Options

MCP Advisor supports two transport methods:

1. Stdio Transport (Default)

Use this for command-line tools and direct integrations.

Add to your AI assistant's MCP configuration to enable service discovery capabilities:

{
"mcpServers": {
   "mcp-advisor": {
      "command": "npx",
      "args": [
         "-y",
         "/path/to/repo/build/index.js"
      ]
   }
}
}

2. SSE Transport (HTTP Server)

Use this for remote servers or web-based integrations. Start the server with:

# Start with SSE transport on port 3000
TRANSPORT_TYPE=sse SERVER_PORT=3000  ENABLE_FILE_LOGGING=true node build/index.js

Environment variables for SSE configuration:

• TRANSPORT_TYPE: Set to sse to use SSE transport (default is stdio)
• SERVER_PORT: HTTP server port (default: 3000)
• SERVER_HOST: HTTP server host (default: localhost)
• SSE_PATH: SSE endpoint path (default: /sse)
• MESSAGE_PATH: Messages endpoint path (default: /messages)

Connect to the server using:

• SSE endpoint: http://localhost:3000/sse
• Messages endpoint: http://localhost:3000/messages?sessionId=<SESSION_ID>
• Health check: http://localhost:3000/health

3. REST Transport

TRANSPORT_TYPE=rest SERVER_PORT=3000  ENABLE_FILE_LOGGING=true node build/index.js

Examples

Example Queries

Here are some example queries you can use with MCP Advisor:

"Find an MCP server for natural language processing"
"MCP server for financial data analysis"
"Recommendation engine MCP server for e-commerce"
"MCP server with image recognition capabilities"
"Weather data processing MCP server"
"Document summarization MCP server"

Example Response

[
  {
    "title": "NLP Toolkit",
    "description": "Comprehensive natural language processing toolkit with sentiment analysis, entity recognition, and text summarization capabilities.",
    "github_url": "https://github.com/example/nlp-toolkit",
    "similarity": 0.92
  },
  {
    "title": "Text Processor",
    "description": "Efficient text processing MCP server with multilingual support.",
    "github_url": "https://github.com/example/text-processor",
    "similarity": 0.85
  }
]

Troubleshooting

Common Issues

1. Connection Refused

   • Ensure the server is running on the specified port
   • Check firewall settings
   • Verify the host address is correct

2. No Results Returned

   • Try a more general query
   • Check network connectivity to the registry API
   • Verify API endpoints are correctly configured

3. SSE Connection Drops

   • Increase client timeout settings
   • Check server logs for error messages
   • Ensure proper CORS configuration if connecting from a browser

4. Performance Issues

   • Consider adding more specific search terms
   • Check server resources (CPU/memory)
   • Implement caching if making frequent similar queries

Logs

For detailed troubleshooting, check the logs in the logs directory. Enable debug logging with:

DEBUG=true node build/index.js

Environment Variables

MCP Advisor can be configured using the following environment variables:

Variable	Description	Default	Required
TRANSPORT_TYPE	Transport method (stdio, sse, rest)	stdio	No
SERVER_PORT	HTTP server port for SSE/REST transport	3000	No
SERVER_HOST	HTTP server host for SSE/REST transport	localhost	No
SSE_PATH	SSE endpoint path	/sse	No
MESSAGE_PATH	Messages endpoint path	/messages	No
ENDPOINT	REST endpoint path	/rest	No
DEBUG	Enable debug logging	false	No
ENABLE_FILE_LOGGING	Enable logging to files	false	No
LOG_LEVEL	Log level (debug, info, warn, error)	info	No

API Documentation

REST API Endpoints

GET /health

Health check endpoint.

Response:

{
  "status": "ok",
  "version": "1.0.0"
}

GET /sse

Server-Sent Events endpoint for establishing a connection.

Query Parameters:

• None

Response:

• Establishes an SSE connection

POST /messages

Endpoint for sending messages to an established SSE connection.

Query Parameters:

• sessionId (string, required): The session ID of the SSE connection

Request Body:

{
  "jsonrpc": "2.0",
  "method": "callTool",
  "params": {
    "name": "recommend-mcp-servers",
    "arguments": {
      "query": "financial data analysis"
    }
  },
  "id": "1"
}

Response:

{
  "jsonrpc": "2.0",
  "result": {
    "content": [
      {
        "title": "Financial Analytics MCP",
        "description": "Comprehensive financial data analysis toolkit",
        "github_url": "https://github.com/example/financial-mcp",
        "similarity": 0.95
      }
    ]
  },
  "id": "1"
}

POST /rest

REST API endpoint for direct requests (when using REST transport).

Request Body:

{
  "jsonrpc": "2.0",
  "method": "callTool",
  "params": {
    "name": "recommend-mcp-servers",
    "arguments": {
      "query": "financial data analysis"
    }
  },
  "id": "1"
}

Response: Same as /messages endpoint.

Test

with inspector

 npx @modelcontextprotocol/inspector

License

MIT License - See LICENSE file for details.