File Search MCP is a Rust-based server that enables efficient full-text search within directories, automatically indexing text files and excluding binaries. It supports MCP integration for AI systems, allowing keyword searches and content retrieval through an in-memory Tantivy index for fast and relevant results.
Added on:
Created by:
Apr 08 2025
File Search MCP is a Rust-based server that enables efficient full-text search within directories, automatically indexing text files and excluding binaries. It supports MCP integration for AI systems, allowing keyword searches and content retrieval through an in-memory Tantivy index for fast and relevant results.
Added on:
Created by:
Apr 08 2025
Kurogoma4D
Featured
What is File Search MCP?
File Search MCP is a specialized Model Context Protocol server developed in Rust that offers powerful full-text search functionality inside a filesystem. It indexes text files using the Tantivy search engine, automatically detecting and skipping binary files. The system supports in-memory indexing for quick search and retrieval, and allows users to search for specific keywords across directory structures. Users can also read the content of specific text files, making it a versatile tool for managing and searching large collections of text documents efficiently. This MCP is ideal for integrating with AI assistants and systems that support the protocol, facilitating seamless content discovery and file reading capabilities.
Who will use File Search MCP?
- Developers needing filesystem search
- AI system integrators
- Content management professionals
How to use the File Search MCP?
- Step1: Clone the repository from GitHub
- Step2: Install Rust SDK
- Step3: Build the project with cargo
- Step4: Add the server command path to your MCP settings
- Step5: Run the server to start indexing files
- Step6: Perform search queries or read file content via MCP
File Search MCP's Core Features & Benefits
The Core Features
- Full-text search within directories
- File content reading
- Automatic text file detection
- In-memory indexing with Tantivy
- MCP compatibility
The Benefits
- Fast and relevant search results
- Efficient management of large text collections
- Seamless integration with AI systems
- Excludes binary files for accurate indexing
File Search MCP's Main Use Cases & Applications
- Searching for keywords across project files
- Retrieving specific file contents
- Indexing large codebases or document repositories
FAQs of File Search MCP
Developer
- Kurogoma4D
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
File Systems
Builds supplemental UI and resource files for client apps, enabling rich media asset integration with visual rendering.
Utilizes Jupyter notebooks to interact with MCP servers, filesystems, and memory for complex automation and data tasks.
Enables AI agents to securely read PDF files and extract text, metadata, and page counts via Node.js/TypeScript.
A set of tools for managing and analyzing MCP PDF documents with server and client components.
Provides secure, relative filesystem access for AI agents with batch operations and detailed error reporting.
A Rust-based client for Minecraft patching, enabling file updates and game modifications efficiently.
Provides secure, relative filesystem access for AI agents like Cline and Claude via Node.js server.
A filesystem MCP server enabling an LLM to read and list local directory files for AI integration.
A Node.js MCP server for reading, listing, and searching Excel files within specified directories.
A server for managing plugin communication in Alist, supporting functions like plugin integration and data exchange.