DevMind-MCP-Server

DevMind MCP

An MCP (Model Context Protocol) server that provides deep, structured project context to AI models, enabling them to understand your codebase like a senior developer teammate.

What is DevMind MCP?

DevMind MCP analyzes your codebase and git history to provide AI models with comprehensive context about:

• Project structure and organization
• Function definitions and relationships
• Code dependencies and imports
• Recent changes and development intent
• TODO items and technical debt
• File relationships and dependencies

This allows AI assistants to answer sophisticated questions like:

• "Why does this function exist?"
• "Where should I implement this new feature?"
• "What files are related to this bug?"
• "What's the recent development context for this code?"

Installation

1. Clone this repository:

git clone https://github.com/Manavarya09/DevMind-MCP-Server.git
cd DevMind-MCP-Server

2. Install dependencies:

pip install -r requirements.txt

Usage

1. Navigate to your project directory:

cd /path/to/your/project

2. Run the MCP server:

python /path/to/devmind-mcp/server.py

The server will automatically index your codebase and git history on startup.

MCP Tools

DevMind MCP exposes the following tools to AI models:

get_project_overview

Get a high-level overview of the project structure and statistics.

Example call:

{
  "method": "tools/call",
  "params": {
    "name": "get_project_overview",
    "arguments": {}
  }
}

Response:

{
  "overview": {
    "file_count": 42,
    "total_size": 125000,
    "total_lines": 8500,
    "function_count": 156,
    "todos": {"TODO": 5, "FIXME": 2}
  },
  "description": "This project contains 42 files with 8500 lines of code and 156 functions."
}

search_codebase

Search for functions and code patterns across the codebase.

Example call:

{
  "method": "tools/call",
  "params": {
    "name": "search_codebase",
    "arguments": {
      "query": "authentication"
    }
  }
}

get_function_context

Get detailed information about a specific function including its code, documentation, and related files.

Example call:

{
  "method": "tools/call",
  "params": {
    "name": "get_function_context",
    "arguments": {
      "function_name": "validate_user"
    }
  }
}

explain_recent_changes

Get recent commit history and explanations of changes.

Example call:

{
  "method": "tools/call",
  "params": {
    "name": "explain_recent_changes",
    "arguments": {
      "file_path": "src/auth.py",
      "limit": 5
    }
  }
}

find_related_files

Find files that are related to a given file based on import dependencies.

Example call:

{
  "method": "tools/call",
  "params": {
    "name": "find_related_files",
    "arguments": {
      "file_path": "src/models/user.py"
    }
  }
}

Architecture

DevMind MCP consists of several key components:

• Server (server.py): MCP protocol implementation and request handling
• Context Analyzer (context/analyzer.py): Codebase analysis using AST parsing
• Git Analyzer (analyzers/git_analyzer.py): Git history and commit analysis
• Database (storage/db.py): SQLite storage for indexed data
• Tools (tools/registry.py): MCP tool definitions and implementations

Data Storage

The server uses SQLite to store:

• File metadata (paths, sizes, line counts)
• Function definitions and signatures
• Import dependencies between files
• TODO/FIXME comments
• Git commit history and changes

Data is indexed on server startup and updated as needed.

Requirements

• Python 3.8+
• Git (for repository analysis)
• SQLite3 (built into Python)

Development

To extend DevMind MCP:

1. Add new analysis features in the analyzers/ directory
2. Define new MCP tools in tools/registry.py
3. Update the database schema in storage/db.py as needed
4. Add corresponding data extraction in context/analyzer.py

Future Roadmap

• Support for additional languages (JavaScript, TypeScript, Go)
• Real-time code analysis and incremental indexing
• Integration with issue trackers (GitHub Issues, Jira)
• Code quality metrics and suggestions
• Dependency graph visualization
• Performance profiling data integration

License

MIT License - see LICENSE file for details.

Contributing

Contributions welcome! Please feel free to submit issues and pull requests.