"General search for file-related information" matching MCP servers:

Search local file contents recursively with keyword matching

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Enables intelligent file searching in local directories using natural language queries. Supports searching by file type, filename patterns, and content across multiple formats including PDF, Word, Excel, and text files with AI-powered relevance scoring.

Provides LLMs with full PostgreSQL database access, including tools for query execution, schema management, and data export. It also features a dedicated insights system for storing business memos and supports both local stdio and remote HTTP transport.

Educational MCP server for basic file operations (read/write) via the Model Context Protocol.

Enables local file management through natural language interactions using the Gemini API, with tools for listing, reading, writing, deleting, and updating files.

Windows-first MCP server for deterministic file writes with atomic create, replace, and structured edit operations, preserving encoding and newline styles.

file operation

Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system through a standardized Model Context Protocol interface.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

Enables precise file patching using SEARCH/REPLACE blocks, with mandatory directory sandboxing, automatic Python QA (Ruff/Black/MyPy), and git versioning for rollback.

An MCP server that gives AI agents file system access: read, write, search, hash, directory trees — 12 tools, zero dependencies, pure Python stdlib.

Enables AI agents and LLMs to perform comprehensive file system operations including CRUD, search, archive, hashing, and duplicate detection via the Model Context Protocol.

MCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.

MCP server for file operations with non-UTF-8/Unicode encoding: Cyrillic, CP1251, CP1252, ISO-8859, KOI8 auto-detection

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables saving and managing files in a sandboxed local folder via MCP, with tools for listing, reading, writing, appending, searching, moving, and deleting files and directories.

A secure MCP server for converting documents between Markdown, DOCX, HTML, PDF, and TXT formats within a sandboxed working directory.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

Enables comprehensive file operations including reading, writing, searching, and editing files with advanced features like regex-based replacements, line-specific modifications, and directory-wide search capabilities. Provides 8 robust tools for safe file manipulation with content verification and detailed error handling.