Tea Rags Vector Search
A high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.
What is Tea Rags Vector Search?
Tea Rags Vector Search is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to high-performance mcp server for semantic search and codebase indexing using the qdrant vector database. it features optimized embedding pipelines, ast-aware chunking, and git metadata enrichment for f...
A high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.
This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A high-performance MCP server for semantic search and codeba
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx tea-rags-mcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Tea Rags Vector Search
What is Tea Rags Vector Search?
Tea Rags Vector Search is a Model Context Protocol (MCP) server that high-performance mcp server for semantic search and codebase indexing using the qdrant vector database. it features optimized embedding pipelines, ast-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Tea Rags Vector Search?
Follow the installation instructions on the Tea Rags Vector Search GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Tea Rags Vector Search?
Tea Rags Vector Search works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Tea Rags Vector Search free to use?
Yes, Tea Rags Vector Search is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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Browse More Knowledge & Memory MCP Servers
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Set Up Tea Rags Vector Search in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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