Code Context (Semantic Code Search)
БесплатноНе проверенEnables semantic code search and understanding by cloning git repositories, splitting code into semantic chunks, and generating embeddings for natural language
Описание
Enables semantic code search and understanding by cloning git repositories, splitting code into semantic chunks, and generating embeddings for natural language querying of large codebases
README
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
Установка Code Context (Semantic Code Search)
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/fkesheh/code-context-mcpFAQ
Code Context (Semantic Code Search) MCP бесплатный?
Да, Code Context (Semantic Code Search) MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Code Context (Semantic Code Search)?
Нет, Code Context (Semantic Code Search) работает без API-ключей и переменных окружения.
Code Context (Semantic Code Search) — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Code Context (Semantic Code Search) в Claude Desktop, Claude Code или Cursor?
Открой Code Context (Semantic Code Search) на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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