Code Context MCP Server
Provides code context from local git repositories.
Code Context MCP Server
A Model Context Protocol (MCP) server for providing code context from local git repositories. This server allows you to:
- Clone git repositories locally
- Process branches and files
- Generate embeddings for code chunks
- Perform semantic search over code
Features
- Uses local git repositories instead of GitHub API
- Stores data in SQLite database
- Splits code into semantic chunks
- Generates embeddings for code chunks using Ollama
- Provides semantic search over code
Prerequisites
- Node.js (v16+)
- Git
- Ollama with an embedding model
Installation
# Clone the repository
git clone <repository-url>
cd code-context-mcp
# Install dependencies
npm install
# Build the project
npm run build
Configuration
Set the following environment variables:
DATA_DIR: Directory for SQLite database (default: '~/.codeContextMcp/data')REPO_CACHE_DIR: Directory for cloned repositories (default: '~/.codeContextMcp/repos')
Using Ollama
For faster and more powerful embeddings, you can use Ollama:
# Install Ollama from https://ollama.ai/
# Pull an embedding model (unclemusclez/jina-embeddings-v2-base-code is recommended)
ollama pull unclemusclez/jina-embeddings-v2-base-code
Usage
Using with Claude Desktop
Add the following configuration to your Claude Desktop configuration file (claude_desktop_config.json):
{
"mcpServers": {
"code-context-mcp": {
"command": "/path/to/your/node",
"args": ["/path/to/code-context-mcp/dist/index.js"]
}
}
}
Tools
The server provides the following tool:
queryRepo
Clones a repository, processes code, and performs semantic search:
{
"repoUrl": "https://github.com/username/repo.git",
"branch": "main", // Optional - defaults to repository's default branch
"query": "Your search query",
"keywords": ["keyword1", "keyword2"], // Optional - filter results by keywords
"filePatterns": ["**/*.ts", "src/*.js"], // Optional - filter files by glob patterns
"excludePatterns": ["**/node_modules/**"], // Optional - exclude files by glob patterns
"limit": 10 // Optional - number of results to return, default: 10
}
The branch parameter is optional. If not provided, the tool will automatically use the repository's default branch.
The keywords parameter is optional. If provided, the results will be filtered to only include chunks that contain at least one of the specified keywords (case-insensitive matching).
The filePatterns and excludePatterns parameters are optional. They allow you to filter which files are processed and searched using glob patterns (e.g., **/*.ts for all TypeScript files).
Database Schema
The server uses SQLite with the following schema:
repository: Stores information about repositoriesbranch: Stores information about branchesfile: Stores information about filesbranch_file_association: Associates files with branchesfile_chunk: Stores code chunks and their embeddings
Debugging
MAC Mx Series - ARM Architecture Issues
When installing better-sqlite3 on Mac M-series chips (ARM architecture), if you encounter errors like "mach-o file, but is an incompatible architecture (have 'x86_64', need 'arm64e' or 'arm64')", you need to ensure the binary matches your architecture. Here's how to resolve this issue:
# Check your Node.js architecture
node -p "process.arch"
# If it shows 'arm64', but you're still having issues, try:
npm rebuild better-sqlite3 --build-from-source
# Or for a clean install:
npm uninstall better-sqlite3
export npm_config_arch=arm64
export npm_config_target_arch=arm64
npm install better-sqlite3 --build-from-source
If you're using Rosetta, make sure your entire environment is consistent. Your error shows x86_64 binaries being built but your system needs arm64. For persistent configuration, add to your .zshrc or .bashrc:
export npm_config_arch=arm64
export npm_config_target_arch=arm64
Testing Ollama Embeddings
curl http://localhost:11434/api/embed -d '{"model":"unclemusclez/jina-embeddings-v2-base-code","input":"Llamas are members of the camelid family"}' curl http://127.0.01:11434/api/embed -d '{"model":"unclemusclez/jina-embeddings-v2-base-code","input":"Llamas are members of the camelid family"}' curl http://[::1]:11434/api/embed -d '{"model":"unclemusclez/jina-embeddings-v2-base-code","input":"Llamas are members of the camelid family"}'
License
MIT
İlgili Sunucular
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Matter AI
Provides advanced code review, implementation planning, and pull request generation using Matter AI.
Sentry
Interact with the Sentry API to monitor application errors and performance.
Figma (Oficial)
The Figma MCP server brings Figma directly into your workflow by providing important design information and context to AI agents generating code from Figma design files.
Cucumber Studio
Provides LLM access to the Cucumber Studio testing platform for managing and executing tests.
1MCP
A unified MCP server that aggregates multiple MCP servers into a single endpoint.
MiniMax MCP JS
A JavaScript/TypeScript server for MiniMax MCP, offering image/video generation, text-to-speech, and voice cloning.
openEuler MCP Servers
A collection of MCP servers designed to enhance the interaction experience with the openEuler operating system.
OpenAPI Schema Explorer
Token-efficient access to OpenAPI/Swagger specs via MCP Resources
Model Context Protocol (MCP)
Interact with Gibson projects to create/update projects, explain database/API interactions, and write code within your IDE.
DevStandards
Provides AI agents with access to development best practices, security guidelines, and coding standards.