MCP Embedding Search
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Integrations
Provides vector similarity search capabilities for transcript segments stored in a Turso database, retrieving relevant content based on natural language queries without generating new embeddings
mcp-embedding-search
A Model Context Protocol (MCP) server that queries a Turso database containing embeddings and transcript segments. This tool allows users to search for relevant transcript segments by asking questions, without generating new embeddings.
Features
- 🔍 Vector similarity search for transcript segments
- 📊 Relevance scoring based on cosine similarity
- 📝 Complete transcript metadata (episode title, timestamps)
- ⚙️ Configurable search parameters (limit, minimum score)
- 🔄 Efficient database connection pooling
- 🛡️ Comprehensive error handling
- 📈 Performance optimized for quick responses
Configuration
This server requires configuration through your MCP client. Here are examples for different environments:
Cline Configuration
Add this to your Cline MCP settings:
Claude Desktop Configuration
Add this to your Claude Desktop configuration:
API
The server implements one MCP tool:
search_embeddings
Search for relevant transcript segments using vector similarity.
Parameters:
question
(string, required): The query text to search forlimit
(number, optional): Number of results to return (default: 5, max: 50)min_score
(number, optional): Minimum similarity threshold (default: 0.5, range: 0-1)
Response format:
Database Schema
This tool expects a Turso database with the following schema:
The embedding
column should contain vector embeddings that can be
used with the vector_distance_cos
function.
Development
Setup
- Clone the repository
- Install dependencies:
- Build the project:
- Run in development mode:
Publishing
The project uses changesets for version management. To publish:
- Create a changeset:
- Version the package:
- Publish to npm:
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License - see the LICENSE file for details.
Acknowledgments
- Built on the Model Context Protocol
- Designed for efficient vector similarity search in transcript databases
This server cannot be installed
A Model Context Protocol server that searches transcript segments in a Turso database using vector similarity, allowing users to find relevant content by asking questions without generating new embeddings.