Monetize your AI agent with contextual product recommendations

Simple MCP (Model Context Protocol) server that invokes a single Watson Orchestrate agent remotely. The agent is defined once via environment variables or MCP config. Use this when you want a lightweight MCP that only chats with one agent—no tool management, no agent listing, no flows. Just invoke_agent(message) and get_agent().

A lightweight MCP server for interacting with the Windows Operating System.

Access the ZenHub GraphQL API to manage project workflows and enhance productivity.

A Python monorepo for AI-powered project management and productivity servers, utilizing the Claude API.

Markdown-first Notion MCP server with 9 composite tools, 39 actions, and ~77% token reduction via tiered docs.

Automated document processing and extraction

Desktop task manager with clean To Do-style UI and 25+ MCP tools for prioritization, goal tracking, and multi-profile workflows.

The Pulsetic MCP Server connects Pulsetic monitoring with AI agents and MCP-compatible tools, enabling direct access to uptime data, cron monitoring results, incident management workflows, and status page information through the Model Context Protocol (MCP). It allows teams to securely expose operational monitoring data in a structured format, making it easy to build AI-driven automation, monitoring assistants, and intelligent operational workflows without custom middleware.

A modular MCP server for task orchestration, API integration, and knowledge synthesis using a finite state machine.

An MCP server for accessing and analyzing Granola.ai meeting data.