MCP Servers
63,654 MCP servers for AI apps. Filter by category, badge and popularity.
Productivity
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 Smartsheet (beta): https://www.cdata.com/download/download.aspx?sku=BSZK-V&type=beta
The first production MCP server for job applications. 5 composable tools that analyze job postings, match candidate profiles, generate story-driven cover letters using 15+ narrative archetypes, and quality-score results. Supports English, German, Spanish, and Portuguese
A Streamable HTTP Transport for the Model Context Protocol (MCP) suited for frameworks like Hono, enabling real-time communication using Server-Sent Events (SSE) and standard HTTP requests. Implements the MCP Streamable HTTP transport specification for edge-compatible environment
Stateless MCP server that keeps AI-generated characters, locations, and shots consistent across a film/video project — tells your AI assistant where the production stands, a scene's per-shot status, and marks shots fired/locked. For creators using Higgsfield, Runway, Kling, Seeda.
AI-powered meeting scheduling via MCP. Let Claude check your calendar, find mutual availability across companies, and book meetings — all through natural conversation. 6 tools: get_meetings, get_contacts, get_availability, schedule_meeting, get_recommended_slots, natural_language
TaskQueue MCP is a revolutionary enterprise-grade Agent execution engine that uses BullMQ as its core task queue infrastructure, implementing a breakthrough dual-loop decoupled architecture. By decoupling user conversation loops from agent execution loops, the engine can execute complex workflows that last for hours or even days while maintaining complete execution transparency and control.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
