An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.
This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.
MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.
An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone.
Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.
A multi-agent research system that decomposes complex queries into targeted sub-questions, searches the web in parallel, scores source credibility, and synthesizes findings into structured markdown reports.
Guides AI agents through open-source contribution workflows, from finding issues to submitting PRs, while keeping decision-making and coding with the human contributor.
A Python-based agent that integrates research providers (OpenAI, Gemini, DR-Tulu, Open Deep Research) with Claude Code via the Model Context Protocol for automated deep research.
A package manager for AI agents that connects LLMs to a global registry of capabilities, allowing them to autonomously discover, install, and learn new skills from a centralized repository.
Integrates with the skills.sh ecosystem to allow AI coding agents to discover, install, and manage reusable instruction sets. It enables autonomous agents to extend their capabilities with structured skill discovery and full lifecycle management through the Model Context Protocol.
An MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive research tasks via Claude.
Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.
Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.