What file formats can be indexed?

It supports `.txt`, `.md`, `.json`, `.jsonl`, and `.csv` files.

How does the server store vectors?

Vectors are stored locally in a SQLite database via LangChain’s LibSQLVectorStore. The path is configured with the `VECTOR_STORE_PATH` environment variable.

What credentials does it need?

It reads `BASE_LLM_API`, `EMBEDDING_MODEL`, `VECTOR_STORE_PATH`, `CHUNK_SIZE`, `LLM_API_KEY` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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MCP Server — kwanLeeFrmVi/mcp-rag-server

mcp-rag-server is a Model Context Protocol (MCP) server that enables Retrieval Augmented Generation (RAG) capabilities. It empowers Large Language

Local serverstdioTypeScript

What is the MCP Server?

mcp-rag-server is a Model Context Protocol (MCP) server that enables Retrieval Augmented Generation (RAG) capabilities. It empowers Large Language Models (LLMs) to

What the server does

Index documents in .txt, .md, .json, .jsonl, and .csv formats
Customizable chunk size for splitting text
Local vector store powered by SQLite (via LangChain's LibSQLVectorStore)
Supports multiple embedding providers (OpenAI, Ollama, Granite, Nomic)
Exposes MCP tools and resources over stdio for seamless integration with MCP clients

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

How to install the MCP Server

{
  "mcpServers": {
    "rag": {
      "command": "npx",
      "args": ["-y", "mcp-rag-server"],
      "env": {
        "BASE_LLM_API": "http://localhost:11434/v1",
        "EMBEDDING_MODEL": "nomic-embed-text",
        "VECTOR_STORE_PATH": "./vector_store",
        "CHUNK_SIZE": "500"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

Variable	Description	Required
BASE_LLM_API	Configuration value read at startup.	Optional
EMBEDDING_MODEL	Configuration value read at startup.	Optional
VECTOR_STORE_PATH	Filesystem location the server is allowed to use.	Optional
CHUNK_SIZE	Configuration value read at startup.	Optional
LLM_API_KEY	Credential the server authenticates with.	Yes