What is an MCP server?
An MCP server is a program built on the Model Context Protocol that wraps a tool, data source, or API — like file access, a database, or web search — into a capability an AI assistant can discover and call.
Browse MCP servers by category and sort by GitHub stars or newest additions. Open a listing for configuration and setup details.
inclusionAI
Search, understand, reproduce, and improve an idea with ease
splx-ai
A security scanner for your LLM agentic workflows
makafeli
AI assistant integration for n8n workflow automation through Model Context Protocol (MCP). Connect Claude Desktop, ChatGPT, and other AI assistants to n8n for natural language workflow management.
mettamatt
A code reasoning MCP server, a fork of sequential-thinking
salacoste
AI-powered n8n workflow automation through natural language. MCP server enabling Claude AI & Cursor IDE to create, manage, and monitor workflows via Model Context Protocol. Multi-instance support, 17 tools, comprehensive docs. Build workflows conversationally without manual JSON
alfonsograziano
A Node.js–based Model Context Protocol server that spins up disposable Docker containers to execute arbitrary JavaScript.
pottekkat
A Model Context Protocol (MCP) server that enables LLMs to run ANY code safely in isolated Docker containers.
quarkusio
Quarkus LangChain4J Workshop that demonstrates both single AI service capabilities and Agentic AI orchestration
Pimzino
A comprehensive Model Context Protocol (MCP) server providing AI assistants with powerful task management and agent memories capabilities with project-specific storage.
MDalamin5
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.
neuronto
Neuronto Agentic Resource Discovery (ARD) Index. Federated search across every public ARD registry, plus a verified tool index read from each MCP server's own tools/list, hybrid lexical and semantic retrieval, and ARD-Bench.
ifmelate
MCP server that allow LLM in agent mode builds n8n workflows for you
peakmojo
A standalone agent runner that executes tasks using MCP (Model Context Protocol) tools via Anthropic Claude, AWS BedRock and OpenAI APIs. It enables AI agents to run autonomously in cloud environments and interact with various systems securely.
JohanLi233
Python sandboxes for llms
Zhonghao1995
Agentic SWMM is an automated, auditable, and memory-informed framework for reproducible stormwater modelling, integrating QGIS and EPA SWMM through the aiswmm runtime, reusable Skills, and MCP interfaces, with QA verification, provenance tracking, calibration support, and Codex,
iflytek
This a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools.
junfanz1
This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independent
junfanz1
This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independent
angrysky56
An MCP server allowing AI assistants to use a Neo4j knowledge graph as their primary, dynamic instruction manual and long term project memory with adaptive templating and autonomous tool development tools.
Godzilla675
A suite of Model Context Protocol (MCP) servers designed to enhance AI agent capabilities. Provides tools for media search/understanding (images, video), web information retrieval, PDF generation, and PowerPoint presentation creation, enabling agents to interact with diverse data
AzDeltaQQ
This is a very basic implementation of an Mcp-Reasoning-Server for Cursor AI .
CaptainCrouton89
An MCP (Model Context Protocol) server that helps AI assistants (like Claude) break down complex tasks into manageable steps, track progress, and manage a hierarchical task list.
bewt85
An MCP server that allows you to run TypeScript, JavaScript, and Python code in a sandbox on your local machine using the Deno® sandbox. This server provides a controlled environment for executing code with explicit permission controls.
Barqawiz
Multi-Agent AI Orchestration Workshop
hfujikawa77
ArduPilotドローンをAIエージェントから操作するMCPサーバーです。
manolaz
emergency-medicare-planner-mcp-server
danstarns
Turn any JavaScript module into a sandboxed MCP (Model Context Protocol) server with automatic reflection and type inference.
King-Proplan
MCP server that gives Claude persistent project memory — roadmap, session history, and codebase context. Type continue and Claude picks up exactly where you left off
mozicim
# 🐢🚀 Node.js Sandbox MCP ServerThis repository hosts a Node.js server that implements the Model Context Protocol (MCP) for running JavaScript in isolated Docker containers. It allows for on-the-fly npm dependency installation, making it easy to execute code safely and efficient
agenticstore
AgenticStore: The secure toolkit for AI agents. Instantly equip Claude Desktop, Cursor, and Windsurf with 27+ MCP tools, persistent memory, and SearXNG search, all protected by a built-in PII prompt firewall to protect your data from being exposed to AI agents.
jacv888
Aider-MCP-Upgraded is a production-grade multi-agent AI coding system that combines Desktop Commander (DC) investigation capabilities with Aider's implementation power. Features 70%+ token reduction, modular architecture, and intelligent workflow automation through strategic agen
rukshannet
MCP Server for Agentic RAG applications
cyberlife-coder
BrianCusack
LangGraph implementation interacting with a PostgreSQL MCP Server
cloudywu0410
A MCP server that enables LLMs to run python code safely in isolated Docker containers.
hygao1024
EunsuGoh
Simple MCP server with Langgraph.
hhw67865
jamesfalkner
This project uses Quarkus and the Model Context Protocol] to implement a simple agentic app using multiple MCP servers and Quarkus + LangChain4j.
shettysaish20
Using Advanced AI Prompting to enhance LLM planning to solve complex math problems and draw the answer on MSPaint Canvas
tuanknguyen
rezawr
A Python-based Model Context Protocol (MCP) server that enables LLMs to access external tools and resources through a standardized interface.
SKalinin909
Deterministic crypto futures calculations for AI agents. PnL, liquidation, break-even, position sizing and more via MCP.
TheCoder30ec4
This repo is for Praticing the Langgraph,Langchain,AI Automation and other stuff along with these MCP server,client implementation
s1ds1ngh
jack-scott
Playing around with different ways to implement MCP servers
MCP-Mirror
Mirror of
superserve-ai
The Superserve MCP server lets any MCP client create and control isolated cloud sandboxes - each one a Firecracker microVM that boots in seconds. Your agent can run shell commands, read and write files, install dependencies, and expose a running server as a public preview URL, th
shizlie
AI-powered workflow compiler for Cloudflare edge. Compile automation from prose via MCP, run forever without AI tokens. 14 tools, 4 resources.
agentika
A simple Slack bot that uses the OpenAI Agents SDK to interact with the Model Context Protocol (MCP) server.
LKGargProjects
🧠 The Core of Your AI Agents
CDataSoftware
This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Microsoft Planner (beta): https://www.cdata.com/download/download.aspx?sku=UIZK-V&type=beta
jake-ccnh
Planning Center Online MCP Server
302ai
Create a remote sandbox that can execute code/run commands/upload and download files.
peekwez
An MCP server for managing context and memory for a multi-agent task execution based on agentic directed acyclic graph
gcampton
MantleKit Launch Planner helps founders, freelancers, and agencies turn a plain-English SaaS idea into a launch-ready MantleKit setup plan. It recommends the best tier, theme, feature set, install path, and next steps using MantleKit’s real product structure, pricing, themes, and
jnuo
Mobile-first, voice-first AI life planner with native MCP. Connect from your AI assistant to read your agenda, create and reschedule tasks, break goals into dated steps across sections, and remember your priorities across sessions. Everything syncs to your real Salta on phone and
ezequielcasillas1
Arkitect-MCP brings architecture-first reasoning to your AI coding workflow. Instead of jumping straight to refactors, the server scans repo context first — platform, workload, health, and intent — then returns actionable cursorGuidance for the agent to follow.
CodeWever
Commercial trust rails for agent work: scoped work orders, rail execution, receipt verification, Trust Ledger records, and Agent Work History.
ansemin
Common questions about MCP servers, tools, and integrations
An MCP server is a program built on the Model Context Protocol that wraps a tool, data source, or API — like file access, a database, or web search — into a capability an AI assistant can discover and call.
Every server's detail page includes ready-to-paste config snippets for Claude Desktop, Cursor, VS Code, and other common clients — most installs take just a couple of minutes.
Most servers listed here are free and open source. Some wrap third-party APIs (cloud services, paid data providers, etc.) that require your own API key or subscription.
A local MCP server runs on your device and usually connects over stdio, giving you more direct control over data but requiring a runtime and installation. A remote MCP server is hosted by a provider and connects over HTTP, making setup easier while adding network and provider availability dependencies.
Claude Desktop, Claude Code, Cursor, VS Code, Codex, and other AI clients that support the Model Context Protocol can connect to MCP servers. Configuration formats and supported transports vary by client.
Review the source repository, maintenance activity, dependencies, requested permissions, and data-handling documentation before installation, and prefer official or trusted maintainers. Use least-privilege credentials for sensitive access such as files, databases, shells, and production systems.