A Model Context Protocol server that enables LLMs to interact with the Lob.com API for address verification and sending physical mail. It provides 76 tools across 12 resource groups including postcards, letters, checks, and templates with built-in safety features for production use.
Provides LLMs with safe, read-only access to local codebases for searching, reading files, and finding function definitions. All source code remains local, ensuring privacy while enabling AI assistants to explore project structures and functionality.
A TypeScript-based MCP server that executes commands and returns structured outputs.
A local Model Context Protocol server designed to share contextual information between an AI and a user. It primarily provides a tool to retrieve the current date and time in ISO 8601 format based on the server's local timezone.
Enables AI assistants to intelligently search and explore local file systems using native Unix commands (ripgrep, find, ls) with token-optimized output, automatic pagination, and multi-layer security validation.
Connects AI systems to Local Falcon API, enabling access to local SEO reporting tools including scan reports, trend analysis, keyword tracking, and competitor data through the Model Context Protocol.
A powerful MCP server that offers web scraping capabilities unrestricted by robots.txt, supports multiple HTTP methods and custom request Settings.
Enables file system operations such as listing, reading, and creating files within a scoped local project directory. It provides a secure way to manage local files through standardized MCP tools built with FastMCP.
Enables exploration and search of local filesystems using glob pattern matching to find files and grep to search for text patterns within files.
Provides sandboxed access to local filesystem operations including directory and file management, content search with glob and regex patterns, and binary file support with configurable safety limits.
An ollama interface which provides models with MCPs
Enables AI assistants to access and interact with Cursor/VS Code Local History data for file recovery and enhanced context awareness. Provides tools to browse file history, search across snapshots, and restore previous versions of files.
A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.
A local RAG-powered documentation search system that uses vector embeddings and Qdrant to enable semantic search across markdown, HTML, and other file formats. It provides an MCP interface for AI tools like Cursor to intelligently query and retrieve information from local knowledge bases.
Bridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.
Enables monitoring and analysis of local application log files with real-time tailing, error tracking, and search capabilities. Perfect for debugging Node.js applications, web servers, or any application that writes to log files through natural language commands.
A MCP server which loads the man pages of tools in $PATH as resource. The goal is to provide the LLM with context of the commands on the host machine
Connect Claude, Cursor, Windsurf and other AI agents to macOS native apps — Mail, Calendar, Contacts, Reminders, Notes, iMessage, Finder, Safari, OmniFocus, Microsoft Teams, Outlook, OneDrive, Word, Excel, PowerPoint, and PDF. 82 tools. All data stays on your Mac.
This is a sample local MCP server.
ローカルMCPサーバー（stdio）を作成するためのチュートリアルです。
