MCP-LOCAL-RAG: Zero APIs, Full Control

MCP-LOCAL-RAG: Deploy RAG-like web search locally with the MCP protocol – zero APIs, full control, and seamless context integration. ✨

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✨ Research And Data

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About MCP-LOCAL-RAG

What is MCP-LOCAL-RAG: Zero APIs, Full Control?

MCP-LOCAL-RAG is a self-contained, RAG-inspired web search model protocol designed for local execution. Built on the Model Context Protocol (MCP) framework, it eliminates reliance on third-party APIs, granting developers complete control over data sourcing and processing workflows. By leveraging UV execution environments, this solution empowers users to deploy advanced search capabilities directly within their local infrastructure.

How to Use MCP-LOCAL-RAG: Zero APIs, Full Control?

Implementing MCP-LOCAL-RAG involves three core steps:
1. Install the UV runtime environment via its official documentation.
2. Configure your Claude setup with provided server parameters (direct injection or repository cloning options available).
3. Execute the protocol using specified commands to initiate the search model.
When prompting for web-related queries, the system automatically triggers context-aware searches through the local rag_search engine, delivering real-time results without external dependencies.

MCP-LOCAL-RAG Features

Key Features of MCP-LOCAL-RAG: Zero APIs, Full Control?

API-Independent Architecture: No cloud service subscriptions or API keys required
Full Local Execution: End-to-end processing occurs within your private environment
Customizable Workflows: Modify search parameters and response logic through modular configuration
Real-Time Capabilities: Access latest web data not available in static knowledge bases

Use Cases of MCP-LOCAL-RAG: Zero APIs, Full Control?

Optimize scenarios requiring:
• Rapid access to emerging technologies and product updates (e.g., model releases)
• Secure internal data searches without exposing sensitive information
• Development environments needing deterministic search outcomes
• Educational or research contexts where data sovereignty is critical

MCP-LOCAL-RAG FAQ

FAQ from MCP-LOCAL-RAG: Zero APIs, Full Control?

Q: What technical prerequisites are required?
A: Only Python 3.8+ and UV runtime installation are needed

Q: Can I update search sources?
A: Yes, customize data pipelines via configuration files

Q: Does it support Windows/Linux/macOS?
A: Fully cross-platform through UV's compatibility layer

Q: How does performance scale?
A: Query response times depend on local hardware and configured data indices

Content

mcp-local-rag

"primitive" RAG-like web search model context protocol (MCP) server that runs locally. ✨ no APIs ✨

Installation instructions

You would need to install uv: https://docs.astral.sh/uv/

If you do not want to clone in Step 2.

Just paste this directly into Claude config. You can find the configuration paths here: https://modelcontextprotocol.io/quickstart/user

{
    "mcpServers": {
        "mcp-local-rag":{
            "command": "uvx",
            "args": [
            "--python=3.10",
            "--from",
            "git+https://github.com/nkapila6/mcp-local-rag",
            "mcp-local-rag"
            ]
        }
    }
}

Otherwise:

Clone this GitHub repository (OPTIONAL, can be skipped with above config)

git clone https://github.com/nkapila6/mcp-local-rag

Add the following to your Claude config. You can find the configuration paths here: https://modelcontextprotocol.io/quickstart/user

{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "uv",
      "args": [
        "--directory",
        "<path where this folder is located>/mcp-local-rag/",
        "run",
        "src/mcp_local_rag/main.py"
      ]
    }
  }
}

Example use

On prompt

When asked to fetch/lookup/search the web, the model prompts you to use MCP server for the chat.

In the example, have asked it about Google's latest Gemma models released yesterday. This is new info that Claude is not aware about.

Result

The result from the local rag_search helps the model answer with new info.