mcp-vectordb-optimizer

movetz/mcp-vectordb-optimizer

3.4

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MCP server for the vector DB tuning and optimization.

The MCP VectorDB Optimizer is a specialized server designed to enhance the performance and efficiency of vector databases. Vector databases are crucial for handling high-dimensional data, often used in machine learning and AI applications. The optimizer focuses on tuning and optimizing these databases to ensure they operate at peak performance. By leveraging advanced algorithms and machine learning techniques, the MCP VectorDB Optimizer can automatically adjust configurations and parameters to suit the specific needs of the database workload. This results in faster query responses, reduced latency, and improved resource utilization. The server is designed to be compatible with various vector database systems, making it a versatile tool for developers and database administrators looking to optimize their data infrastructure.

Features

  • Automated tuning: Automatically adjusts database configurations for optimal performance.
  • Compatibility: Works with a wide range of vector database systems.
  • Performance monitoring: Continuously monitors database performance and suggests improvements.
  • Resource optimization: Enhances resource utilization to reduce costs and improve efficiency.
  • Scalability: Supports scaling of database operations to handle increased workloads.

Usages

usage with local integration stdio

python
mcp.run(transport='stdio')  # Tools defined via @mcp.tool() decorator

usage with local integration ide plugin

{
  "mcpServers": {
    "vectordb-optimizer": {
      "command": "python",
      "args": ["vectordb_optimizer.py"]
    }
  }
}

usage with remote integration sse

python
mcp.run(transport='sse', host="0.0.0.0", port=8000)  # Specify SSE endpoint

usage with remote integration streamable http

yaml
paths:
  /mcp:
    post:
      x-ms-agentic-protocol: mcp-streamable-1.0  # Copilot Studio integration

usage with platform ecosystem integration github

{"command": "docker", "args": ["run", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"]}

usage with platform ecosystem integration copilot studio

yaml
paths:
  /mcp:
    post:
      x-ms-agentic-protocol: mcp-streamable-1.0  # Copilot Studio integration