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An MCP server that publishes CLI tools on your machine for discoverability by LLMs

Real-time web search and crawling capabilities for AI assistants through Model Context Protocol (MCP)

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

Model Context Protocol server that integrates AgentQL's data extraction capabilities.

Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors

Vector Memory MCP Server A secure, vector-based memory server for Claude Desktop using sqlite-vec and sentence-transformers. This MCP server provides persistent semantic memory capabilities that enhance AI coding assistants by remembering and retrieving relevant coding experiences, solutions, and knowledge. ✨ Features 🔍 Semantic Search: Vector-based similarity search using 384-dimensional embeddings 💾 Persistent Storage: SQLite database with vector indexing via sqlite-vec 🏷️ Smart Organization: Categories and tags for better memory organization 🔒 Security First: Input validation, path sanitization, and resource limits ⚡ High Performance: Fast embedding generation with sentence-transformers 🧹 Auto-Cleanup: Intelligent memory management and cleanup tools 📊 Rich Statistics: Comprehensive memory database analytics 🔄 Automatic Deduplication: SHA-256 content hashing prevents storing duplicate memories 📈 Access Tracking: Monitors memory usage with access counts and timestamps for optimization 🧠 Smart Cleanup Algorithm: Prioritizes memory retention based on recency, access patterns, and importance

An MCP Server that enables integration of AI assistants with the Simplifier Low Code Platform. It provides tools and resources for creating and managing Simplifier Connectors and BusinessObjects.

Flag features directly from chat in your code editor, including VS Code, Cursor, Windsurf, Claude Code—any IDE with MCP support.

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

summarize chat message

Read-only database access with schema inspection

org-mcp is an Emacs package that implements a Model Context Protocol (MCP) server for Org-mode. It enables AI assistants and other MCP clients to interact with your Org files through a structured API.

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

A lightweight MCP (Model Context Protocol) server built to query Postgres database. It provides comprehensive tools for database operations, table introspection, and query execution with smart permission handling.

The World's First AI Music MCP Beyond images and video, your agent can now generate music.

Manage Pi-hole with the power of AI A Pi-hole MCP (Model Control Protocol) server implemented in Java that allows AI applications to interact with and manage a Pi-hole instance through standard commands.

Stops AI from writing duplicate code. Forces Claude/Cursor/Windsurf to analyze existing code first, get approval on plans, then execute step-by-step. Engineering gates ensure no hallucinations or breaking changes.

An MCP server that provides a tool for sending transactional emails via Mailtrap

高德地图官方 MCP Server

零负担、开箱即用的模型上下文协议（MCP）服务器，用于与 MySQL 交互和自动化操作。无需 Node.js 或 Python 环境。该服务器提供对 MySQL 数据库和表进行 CRUD 操作的工具，以及只读模式以防止意外的写入操作。您还可以通过添加 --with-explain-check 标志让 MCP 服务器在执行查询前使用 EXPLAIN 语句检查查询计划。

Retrieving and analyzing issues from Sentry.io

Execute Python, JavaScript, Bash, and Go code in isolated cloud containers with sub-150ms startup times. Pre-installed data science libraries (pandas, numpy, matplotlib) for AI-powered data analysis and code testing.

A Model Context Protocol (MCP) server that brings your Withings health data into MCP client. Access your sleep patterns, body measurements, workouts, heart data, and more through natural conversation. 🔒 Privacy First: This is my personal project, and the repository is intentionally public to demonstrate transparency. The code shows that no personal information is logged or stored maliciously. All sensitive data (tokens, user IDs) is encrypted at rest and automatically redacted from logs. You can review the entire codebase to verify this commitment to privacy. ⚠️ Disclaimer: This server is provided as-is without any guarantees or warranties. While I've made every effort to ensure security and privacy, I make no guarantees about availability, data integrity, or security. Use at your own risk. For production use cases, consider self-hosting your own instance.

Loop your agents into environment management, and give them access/context to run tests, tail environment logs, start/stop environments, and debug remote issues.

Web content fetching and conversion for efficient LLM usage