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

Enables fast file search on macOS using the native mdfind (Spotlight) command, with support for filtering, regex, sorting, and limiting results.

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 natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

An MCP server that enables file system search and inspection, including directory listing, regex-based file name and content searches, and reading text, PDF, and DOCX files.

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.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

Enables semantic search over personal files using natural language, with optional AI summarization, all running locally.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

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

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

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

Local-first filesystem MCP bridge with ripgrep search, atomic writes, multiple transports

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A powerful, security-hardened MCP server for intelligent file organization. Provides high-level atomic tools for organizing files into categories, detecting duplicates, extracting EXIF/ID3 metadata, scheduling automatic organization, and more — for use with Claude, Cursor, and Gemini CLI.

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

Enables Claude Desktop to download files from web URLs with automatic browser fallback for JavaScript-heavy sites. Supports smart redirect handling, custom file naming, and cross-platform compatibility.

A MCP server that allows searching for files in the filesystem based on path fragments, returning file metadata including name, path, size, and creation date.

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.

Provides AI agents with document conversion to Markdown, intelligently routing small and large files, and enabling targeted extraction via sections, search, and token budgets.

Enables Codex to locate QQ groups by name or number and search group file directories and recent chat attachments by filename, then download selected files through a locally deployed NapCat instance, returning paths, sizes, and SHA-256 hashes.

MCP server for converting between everyday file formats (CSV, Excel, Markdown, Word), including a GxP-compliant Markdown to Word template. Exposes four conversion tools over stdio.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables file operations (PDF, Office, images, archives, media) through natural language, with tools for reading, writing, converting, and analyzing files locally.

Enables uploading local files to Slack with a message, supporting channels, DMs, threads, and file titles.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.