mcp — MCP Server by mondaycom

by mondaycom · MCP Server · ★ 411

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

About mcp

🚀 monday.com MCP Enable AI agents to operate reliably within real workflows. This MCP is monday.com's open framework for connecting agents into your work OS - giving them secure access to structured data, tools to take action, and the context needed to make smart decisions. 🌟 Overview This repository, maintained by the monday.com AI team, provides a comprehensive set of tools for AI agent developers who want to integrate with monday.com. Whether you're building AI assistants, automations, or custom integrations, our tools make

agentscopilotmcpmcp-servermonday

Quick Facts

Stars411
Forks82
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score71.5080512630968/100
Open Issues39
Last Updated2026-06-24
Created2025-04-06
Platformsmcp, node
Est. Tokens~18k

mcp alternative? Top 6 similar tools

Looking for a mcp alternative? If you're comparing mcp with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is mcp?

mcp is Enable AI agents to work reliably - giving them secure access to structured data, tools to take action, and the context needed to make smart decisions.. It is categorized as a MCP Server with 411 GitHub stars.

What programming language is mcp written in?

mcp is primarily written in TypeScript. It covers topics such as agents, copilot, mcp.

How do I install or use mcp?

You can find installation instructions and usage details in the mcp GitHub repository at github.com/mondaycom/mcp. The project has 411 stars and 82 forks, indicating an active community.

What license does mcp use?

mcp is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to mcp?

The top alternatives to mcp on Agent Skills Hub include toolhive-studio, npcpy, apify-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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