vector

Vector MCP Server provides a standardized interface for interacting with vector database backends through MCP Tools. The server exposes tools such as create_collection, semantic_search, add_documents, delete_collection, and list_collections, enabling you to manage vector collections and perform retrieval-augmented generation (RAG) workflows across supported backends like ChromaDB, PGVector, Couchbase, Qdrant, and MongoDB. The A2A architecture runs atop Uvicorn/FastAPI, allowing a modular flow where a user query is processed by an agent that can call MCP Tools to manage or query collections and fetch results for downstream tasks. You can invoke the MCP Tools to create or retrieve collections, add documents, perform semantic searches, or delete and enumerate collections as part of your information retrieval or AI-assisted workflows.

Prerequisites:

• Python 3.8+ installed on your system
• Internet access to fetch packages
• Access to a MongoDB/ChromaDB/PGVector/Couchbase/Qdrant service (or local filesystem storage as configured)

Installation steps:

1. Install the MCP server package from PyPI:

pip install vector-mcp

2. Run the MCP server using the uvx runner (provided by the MCP ecosystem):

uvx vector-mcp

3. Verify the server is running by checking the logs or hitting the MCP CLI endpoint if documented. If you need to customize environment variables, set them before starting:

export VECTOR_MCP_CONFIG=/path/to/your/config.json
uvx vector-mcp

Optional: If you prefer using a package manager, you can install uvx via your preferred method and then execute the server with the package name as shown above.

Notes and tips:

• The MCP server supports multiple vector backends; ensure your chosen backend is properly configured and accessible.
• Typical environment variables may include backend connection strings, authentication details, and path to your collection storage.
• If you encounter port or host binding issues, verify your network settings and adjust any transport-related options in your MCP configuration.
• When upgrading, review breaking changes in the MCP Tools API or backend adapters to avoid runtime errors.
• The npm_package field is null since this is a Python-based server.
• If you plan to run multiple MCP servers, consider using distinct host/port combinations and per-server configuration files.