This MCP server wraps ripgrep search capabilities into a Model Context Protocol (MCP) interface, allowing MCP clients such as Claude AI to perform high-performance text searches across local files. It integrates with Node.js and requires ripgrep to be installed, supporting advanced search functionalities and file listing operations.
Added on:
Created by:
Apr 07 2025
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What is MCP Ripgrep Server?
The MCP Ripgrep Server offers a high-performance text search solution via an MCP interface by leveraging ripgrep. It allows clients to perform quick and efficient content searches across files on the system. The server supports basic and advanced search commands, listing files and file types, and counting pattern matches, making it ideal for developers, system administrators, and AI integrations needing fast search capabilities. It requires Node.js (v18+) and ripgrep to work effectively, providing a flexible and powerful tool for managing large codebases or file collections.
Who will use MCP Ripgrep Server?
- Developers
- System Administrators
- AI Integrations
- Researcher
- Codebase Maintainers
How to use the MCP Ripgrep Server?
- Step 1: Install Node.js (v18 or higher)
- Step 2: Install ripgrep (`rg`) command and ensure it’s in your PATH
- Step 3: Clone or download the MCP Ripgrep Server repository
- Step 4: Run the server using Node.js
- Step 5: Configure your MCP client (like Claude) to connect to the server
- Step 6: Use search, advanced-search, list-files, etc., commands via MCP interface
MCP Ripgrep Server's Core Features & Benefits
The Core Features
- search
- advanced-search
- count-matches
- list-files
- list-file-types
The Benefits
- Fast text searching across files
- Supports complex search patterns
- Easy integration with MCP-compatible clients
- Provides file listing and type support
- Enhances search efficiency for large codebases
MCP Ripgrep Server's Main Use Cases & Applications
- Integrating ripgrep search into AI tools like Claude
- Performing codebase searches for development projects
- System-wide file content indexing and searching
- Automated code quality checks with pattern matching
- Large-scale document analysis and retrieval