"A tool to access websites and extract coding documentation" matching MCP servers:

Enables an AI assistant to reliably read and chunk PDF/text documents, validate extracted JSON against a schema with full error paths, and save structured output—all confined to a single allowed directory.

Experimental MCP server for local LLM orchestration with filesystem tools (read, write, list, delete files) and a CLI agent that communicates via Ollama.

FastMCP server for PDF text extraction and metadata retrieval, providing structured JSON output for pages, metadata, and specific page ranges.

Enables cloud services with MCP support, such as Notion AI, to read, search, edit, create, and delete files within a single designated folder on your computer, and to run only allowed commands.

Provides safe repository operations, skill reading, command execution, and test detection for coding agents over stdio.

AI-powered MCP server for file renaming, organization, and PDF splitting using natural language prompts and content analysis.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

Provides coding agent capabilities including file operations, terminal commands, search functionality, and utility operations.

Gives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.

Enables AI agents to develop within a local project workspace by reading and modifying files, running commands and tests, checking Git state, and persisting progress as history sessions that can be restored in later conversations.

Gives MCP-compatible AI clients safe, hands-on access to local codebases: file reading/search, multi-file patches, command execution, interactive sessions, Git inspection, and coordination of local agent providers such as Antigravity and OpenCode.

A Rust + Tauri 2 desktop application that turns local project folders into persistent MCP workspaces, enabling AI agents to read files, modify code, run commands and tests, check Git status, and maintain cross-conversation development context through historical checkpoints, with built-in WSS/FRP/Cloudflare tunnels and OAuth for connecting to ChatGPT.

A local MCP server that gives AI coding assistants read, write, search, and execute capabilities within a specified project directory. This Windows GUI build simplifies setup by eliminating manual Python, Node.js, or Docker installation.

Turns any Linux server into an AI-agent-accessible machine over HTTPS, allowing MCP clients like ChatGPT, Claude, and Grok to securely control files, run shell commands, inspect system state, query SQLite, and work with git behind a bearer token.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Enables ChatGPT web to interact with local Windows/WSL shell and code workspaces via an MCP server, providing file access, shell execution, and snapshot-based workspace management with per-command authorization.

Provides full access to a local Windows computer via MCP, enabling arbitrary command execution, file operations, and process management through a secure stdio or HTTP tunnel.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

Local MCP server enabling Codex and ChatGPT to read/write files, execute commands, manage processes, use Git, and inspect images on the user's machine with full privileges.

Turns local project directories into persistent MCP workspaces, allowing AI agents to read files, modify code, run commands, manage Git, and save session progress across conversations.

Enables saving files and folders to a local NAS over NFS with automatic share discovery, smart mounting, and seamless file transfers.

Enables AI agents to convert GitHub Flavored Markdown into formatted Word (.docx) files, including headings, lists, tables, links, code and images, with an optional Chinese official document (公文) font preset. Conversion runs locally, so no content is uploaded.

A TypeScript prototype for an MCP-style registry providing local utility tools for shell command execution, filesystem access, and search functionality. It features Zod input validation and project manifest resource exposure for embedding into larger MCP implementations.

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.

A secure, production-grade MCP server that provides filesystem operations, AST math evaluation, and system diagnostics for LLM agents.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

A modular, extensible MCP multi-server hub that gives LLMs sandboxed file access, Git operations, web fetching, and persistent memory, deployable via Ansible.

A custom MCP server with 6 utility tools (file search, file reading, math calculation, JSON formatting, time query, system info) that demonstrates MCP protocol workflow and integrates with LangChain agents.