Which integrations are available for this server?

Enables indexing and semantic search of local files (PDF, TXT, CSV, Markdown, etc.) using embeddings and optional FAISS indexing for fast similarity-based document retrieval

How do I use MCP Data Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Data Server search for documents about Python virtual environments" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Data Server — Local file search you can call from Claude (or CLI)

MCP Data Server indexes files on your machine (PDF, TXT, CSV, Markdown, etc.) and lets you search them with embeddings. You can use it from:

a friendly CLI (ls, index, search)
an MCP server over stdio (so Claude Desktop/Cursor can call your tools)

Works great on Windows 11. Also tested on macOS/Linux (see notes).

Features

🔎 Local search with SentenceTransformers embeddings (cosine similarity)
⚡ Optional FAISS index for fast Top-K search
🧰 Simple CLI: ls, index, search
🔌 MCP server so Claude Desktop can call tools: list_docs_tool, index_docs_tool, search_chunks_tool, read_doc_tool
🧩 Extensible loaders/chunkers; add new formats easily
✅ Batteries-included dev setup: Ruff, Black, MyPy, PyTest, pre-commit

Prerequisites

Python 3.11+ (3.11 recommended)
Windows 11 (PowerShell) macOS/Linux are fine too (bash)
~3 GB free disk space on first run (model cache)
(Optional) FAISS CPU wheels installed automatically via faiss-cpu

Quick start (Windows)

Folder in this repo where you put files to index: ./data/

# 1) Clone and enter project git clone https://github.com/hkonda015/McpServer.git Set-Location .\McpServer\McpServer # 2) Create & activate venv (PowerShell) python -m venv .venv .\.venv\Scripts\Activate.ps1 # 3) Install runtime (or dev) dependencies pip install -r requirements.txt # or for contributors: pip install -r requirements-dev.txt # 4) (Optional) pre-commit hooks pre-commit install # 5) Put a few files in .\data\ (txt/pdf/csv/md), then: python -m mcp_data_server ls python -m mcp_data_server index python -m mcp_data_server search "your query" --k 5 ## Usage (CLI) The CLI lets you **list files**, **build/rebuild the index**, and **search** your local documents. > **Prereq:** open a terminal at your repo root and activate the venv > Windows (PowerShell): > ```powershell > Set-Location .\McpServer > .\.venv\Scripts\Activate.ps1 > ``` > macOS/Linux (bash): > ```bash > cd McpServer > source .venv/bin/activate > ``` --- ### 1) List files (`ls`) Lists all **supported documents** under `DATA_DIR` (defaults to `./data`). ```powershell python -m mcp_data_server ls # Contributing to MCP Data Server Thanks for your interest in contributing! This document explains how to set up your dev environment, the coding standards we use, how to run tests, and how to submit a good pull request. --- ## Ways to contribute - **Bug reports**: include steps to reproduce, expected vs actual behavior, OS, Python version, and logs. - **Feature requests**: explain the use case, not just the solution. Sketch CLI and/or MCP tool UX if relevant. - **Documentation**: improve READMEs, examples, and comments. - **Code**: bug fixes, new loaders, chunking strategies, performance improvements, tests. Good first issues will be labeled **good first issue** and **help wanted**. --- ## Development setup ### Prerequisites - Python **3.11+** (we recommend 3.11) - Git - ~3 GB free disk space for model cache on first run ### Clone and create a virtual environment #### Windows (PowerShell) ```powershell git clone https://github.com/hkonda015/McpServer.git Set-Location .\McpServer\McpServer python -m venv .venv .\.venv\Scripts\Activate.ps1 pip install -r requirements-dev.txt pre-commit install