Code Vector Sync
FreeNot checkedEnables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible c
About
Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.
README
An MCP (Model Context Protocol) server that provides semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings. Point it at a directory and query it with natural language from any MCP-compatible client (e.g., Claude Desktop).
What It Does
- Watches a local directory for file changes and auto-indexes them
- Embeds code using OpenAI's embedding API
- Stores vectors in a Qdrant cloud collection
- Serves semantic search results via the MCP protocol
Architecture
File Watcher → Embedding Service → Qdrant Manager
↑
MCP Client (Claude) ←── MCP Server ────┘
(code_search)
Setup
1. Install dependencies
pip install -r requirements.txt
2. Configure environment
cp .env.example .env
# Edit .env with your Qdrant URL, Qdrant API key, OpenAI API key, and watch directory
3. Run the MCP server
python run_mcp_server.py
4. Connect to Claude Desktop
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"code-vector-search": {
"command": "python",
"args": ["/path/to/code-vector-sync/run_mcp_server.py"],
"env": {
"QDRANT_URL": "your-qdrant-url",
"QDRANT_API_KEY": "your-api-key",
"OPENAI_API_KEY": "your-openai-key"
}
}
}
}
Project Structure
code-vector-sync/
├── src/
│ ├── mcp_server.py # MCP server entry point and tool definitions
│ ├── code_search.py # Search query handling
│ ├── code_sync_service.py # Orchestrates watching, embedding, and indexing
│ ├── embedding_service.py # OpenAI embedding calls
│ ├── file_watcher.py # Watchdog-based directory monitoring
│ └── qdrant_manager.py # Qdrant client and collection management
├── run_mcp_server.py # Launcher script
├── requirements.txt
├── .env.example # Template — copy to .env and fill in values
└── .gitignore
Requirements
- Python 3.10+
- Qdrant Cloud account (free tier works)
- OpenAI API key
Related Projects
- agent-dev — Containerized AI agent dev environment that this server is designed to complement
Installing Code Vector Sync
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/Abernaughty/code-vector-syncFAQ
Is Code Vector Sync MCP free?
Yes, Code Vector Sync MCP is free — one-click install via Unyly at no cost.
Does Code Vector Sync need an API key?
No, Code Vector Sync runs without API keys or environment variables.
Is Code Vector Sync hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Code Vector Sync in Claude Desktop, Claude Code or Cursor?
Open Code Vector Sync on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
GitHub
PRs, issues, code search, CI status
by GitHubFilesystem
Secure file operations with configurable access controls.
Memory
Knowledge graph-based persistent memory system.
Template MCP Server
A CLI tool to create a new Model Context Protocol server project with TypeScript support, dual transport options, and an extensible structure
by mcpdotdirectCompare Code Vector Sync with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All development MCPs
