agent-rag-mcp 1.1.1

RAG MCP server: ChromaDB + sentence-transformers, exposes ingest/search/list/delete tools.

Agent_rag

Agent_rag is a RAG (Retrieval-Augmented Generation) MCP (Model Context Protocol) Server. It uses ChromaDB and sentence-transformers locally to provide a vector store for your intelligent agents.

This server exposes several tools for the orchestrator (Agent_head) or any other MCP client to call:

• rag_ingest: Ingest documents, directories, or raw text into a collection.
• rag_search: Semantic search against the ingested knowledge base.
• rag_list_collections: List all active collections.
• rag_delete_collection: Delete a specific collection.

Features

• Local Embeddings: Uses sentence-transformers (default: all-MiniLM-L6-v2) locally, meaning no API keys or external services are required for embedding generation.
• FastMCP Built-in: Asynchronous and thread-safe tool execution using FastMCP.
• Easy Configuration: Configurable via config.yaml to set your desired chunk size, collection names, and embedding models.

Installation & Usage

Agent_rag is packaged and distributed via standard Python mechanisms. You can run it effortlessly using uv without needing to clone the repository or manually manage virtual environments.

Running with uvx

You can run the MCP server directly. uvx will automatically download and run the latest version of the agent-rag-mcp CLI:

uvx agent-rag-mcp

Transport Modes By default, the server runs in stdio transport mode (designed to be spawned as a subprocess by MCP clients like Agent_head).

To run it over HTTP using Server-Sent Events (SSE):

uvx agent-rag-mcp --transport sse --port 8002 --host 0.0.0.0

Specifying a Test Registry (If using TestPyPI)

If you published the package to: TestPyPI instead of the main PyPI, run it via

uvx --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match agent-rag-mcp@latest

Integrating with Agent_head

To connect this RAG server to your Agent_head orchestrator, add the following configuration to your Agent_head/config.yaml:

memory:
  enabled: true
  backend: "rag"

  # Configure this if backend is set to "rag"
  rag_server:
    command: "uvx"
    args: ["agent-rag-mcp"] # Or ["--from", "/path/to/local/Agent_rag", "agent-rag-mcp"] for local development
    collection: "agent_memory"

Local Development

If you are developing this package locally:

1. Install dependencies:

   uv sync
   

2. Run locally:

   uv run agent-rag-mcp
   

3. Build the package:

   uv build