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second-opinion-mcp-server

MCP.Pizza Chef: PoliTwit1984

The second-opinion-mcp-server is an advanced MCP server designed to provide comprehensive AI-assisted solutions for coding problems. It integrates insights from Google's Gemini AI, Stack Overflow accepted answers, and Perplexity AI analysis to deliver detailed, context-aware coding help. Features include automatic programming language detection from file extensions, code snippet extraction and formatting, markdown report generation, and git-aware file context gathering. This server enhances developer productivity by aggregating multiple expert sources into a single, structured response, making it ideal for real-time coding assistance and debugging workflows.

Use This MCP server To

Provide AI-assisted coding problem solutions Aggregate coding insights from multiple AI and community sources Automatically detect programming language from file extensions Extract and format code snippets for clarity Generate markdown reports summarizing coding solutions Gather git-aware file context for accurate problem analysis

README

Second Opinion MCP Server

An MCP server that provides AI-powered assistance for coding problems by combining insights from:

  • Google's Gemini AI
  • Stack Overflow accepted answers
  • Perplexity AI analysis

Features

  • Get detailed solutions for coding problems with context from multiple sources
  • Automatic language detection from file extensions
  • Code snippet extraction and formatting
  • Markdown report generation for solutions
  • Git-aware file context gathering

Setup

  1. Install dependencies:
npm install
  1. Build the server:
npm run build
  1. Configure environment variables in MCP settings:
{
  "mcpServers": {
    "second-opinion": {
      "command": "node",
      "args": ["/path/to/second-opinion-server/build/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-gemini-api-key",
        "PERPLEXITY_API_KEY": "your-perplexity-api-key",
        "STACK_EXCHANGE_KEY": "your-stack-exchange-key"
      }
    }
  }
}

Required environment variables:

  • GEMINI_API_KEY: Google's Gemini AI API key
  • PERPLEXITY_API_KEY: Perplexity AI API key
  • STACK_EXCHANGE_KEY: Stack Exchange API key (optional, uses anonymous access if not provided)

Usage

The server provides a single tool:

get_second_opinion

Get AI-powered insights and solutions for coding problems.

Input Schema:

{
  "goal": "string (required) - What you're trying to accomplish",
  "error": "string (optional) - Any error messages you're seeing",
  "code": "string (optional) - Relevant code context",
  "solutionsTried": "string (optional) - What solutions you've already tried",
  "filePath": "string (optional) - Path to the file with the issue"
}

Example Input:

{
  "goal": "Fix React useEffect cleanup error",
  "error": "React Hook useEffect has a missing dependency: 'socket'. Either include it in the dependency array, or remove the dependency array  react-hooks/exhaustive-deps",
  "code": "useEffect(() => {\n  socket.on('message', handleMessage);\n  return () => socket.off('message');\n}, []);",
  "solutionsTried": "I tried adding socket to the dependency array but then it causes infinite re-renders"
}

Example Response:

Understanding the Problem

The core issue lies in how React's useEffect hook manages side effects and their dependencies. When you provide an empty dependency array ([]), you're telling React that the effect should only run once when the component mounts and that the cleanup function should run when the component unmounts.

However, in your code, the socket object is used within the effect. This creates a closure where the handleMessage function and the cleanup function (socket.off('message')) implicitly depend on the current value of socket. If socket ever changes (e.g., due to a reconnection or reinitialization), your effect will be using an outdated socket instance.

Common Issues

  • Stale Closures: The event handler (handleMessage) might be working with an old socket object
  • Incorrect Cleanup: The socket.off('message') might not remove the intended event listener
  • Memory Leaks: Failed cleanup can lead to memory leaks and unexpected behavior

Solutions

1. Using useRef for Stable References

import React, { useEffect, useRef } from 'react';

function MyComponent({ socket }) {
  const socketRef = useRef(socket);

  useEffect(() => {
    const currentSocket = socketRef.current;
    currentSocket.on('message', handleMessage);
    return () => {
      currentSocket.off('message');
    };
  }, []); // Empty dependency array is now safe
}

Why This Works:

  • useRef creates a mutable object that persists across renders
  • The ref object itself doesn't change, preventing effect re-runs
  • You can access the latest socket value via the ref

2. Using useCallback for Handlers

import React, { useEffect, useRef, useCallback } from 'react';

function MyComponent({ socket, someProp }) {
  const socketRef = useRef(socket);

  const handleMessage = useCallback((message) => {
    // Do something with the message and potentially someProp
    console.log(message, someProp);
  }, [someProp]); // Include dependencies of handleMessage

  useEffect(() => {
    const currentSocket = socketRef.current;
    currentSocket.on('message', handleMessage);
    return () => {
      currentSocket.off('message', handleMessage);
    };
  }, [handleMessage]); // Depend on the memoized handler
}

3. Managing Socket Lifecycle Inside useEffect

import React, { useEffect, useState } from 'react';

function MyComponent() {
  const [messages, setMessages] = useState([]);

  useEffect(() => {
    const socket = new WebSocket('your_websocket_url');

    const handleMessage = (message) => {
      setMessages((prevMessages) => [...prevMessages, message]);
    };

    socket.on('message', handleMessage);

    return () => {
      socket.off('message', handleMessage);
      socket.close();
    };
  }, []); // Empty array is correct - socket lifecycle managed within
}

4. Custom Hook Solution

function useSocket(url) {
  const [messages, setMessages] = useState([]);
  const socketRef = useRef(null);

  useEffect(() => {
    const socket = new WebSocket(url);
    socketRef.current = socket;

    const handleMessage = (message) => {
      setMessages((prevMessages) => [...prevMessages, message]);
    };

    socket.on('message', handleMessage);

    return () => {
      socket.off('message', handleMessage);
      socket.close();
    };
  }, [url]);

  const sendMessage = useCallback((message) => {
    if (socketRef.current?.readyState === WebSocket.OPEN) {
      socketRef.current.send(message);
    }
  }, []);

  return { messages, sendMessage };
}

Best Practices

  1. Dependency Management

    • Use useRef for stable references
    • Memoize handlers with useCallback
    • Consider socket lifecycle management
  2. Performance Optimization

    • Minimize unnecessary re-renders
    • Handle high-volume messages efficiently
    • Use appropriate cleanup patterns
  3. Error Handling

    • Handle connection errors gracefully
    • Implement reconnection logic if needed
    • Clean up resources properly
  4. Testing Considerations

    • Mock WebSocket connections in tests
    • Verify event listener cleanup
    • Test error scenarios

Project Structure

src/
├── config.ts        # Configuration and API settings
├── fileUtils.ts     # File operations and language detection
├── index.ts         # Entry point
├── perplexity.ts   # Perplexity AI integration
├── server.ts       # MCP server implementation
├── stackOverflow.ts # Stack Overflow API integration
└── types.ts        # TypeScript interfaces

Known Issues

See errors.md for current issues and workarounds.

second-opinion-mcp-server FAQ

How do I install the second-opinion-mcp-server?
Install dependencies with 'npm install', then build the server using 'npm run build'.
What environment variables are required to run this MCP server?
You need GEMINI_API_KEY, PERPLEXITY_API_KEY, and STACK_EXCHANGE_KEY set in your MCP server environment.
Can this server detect the programming language automatically?
Yes, it detects the language automatically based on file extensions.
How does the server gather context for coding problems?
It uses git-aware file context gathering to provide relevant code context.
What output formats does the server support?
It generates markdown reports that summarize the coding solutions with formatted code snippets.
Is this MCP server compatible with multiple LLM providers?
While it primarily integrates Gemini AI, it also leverages insights from Perplexity AI and Stack Overflow data.
How do I configure the server in MCP settings?
Configure the command, arguments, and environment variables in your MCP settings JSON as shown in the setup instructions.
Can this server help with debugging as well as coding?
Yes, by providing detailed solutions and context-aware insights, it assists in both coding and debugging tasks.