"Collaboration Between Multiple AIs via MCP (Master Control Program)" matching MCP servers:

A Firecrawl MCP server with built-in support for multiple API key rotation, enabling web search, scraping, crawling, extraction, and more via MCP clients.

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

MCP server bridging product ideas to prioritized roadmaps + spec drafts. Hands directly off to mk-spec-master. (AI 規劃大師)

MCP server for the Production Master incident-investigation service, enabling any MCP client to drive investigations via tool calls with pass-through authentication.

Enables collaboration with multiple AI providers (Claude, GPT-4, Gemini, Ollama) directly from VS Code with automatic project context injection and persistent conversation history. Provides streamlined tools for getting AI advice, multi-provider research, and enhanced context sharing across sessions.

Enables AI agents to interact with collaborative Jupyter notebooks and documents in real-time, supporting notebook operations, document editing, user awareness tracking, and session management through Jupyter's RTC capabilities.

Aggregates multiple MCP servers behind a single, secure endpoint with unified tool/resource discovery, OAuth authentication, and resilient request routing. Enables users to manage and interact with multiple MCP backends through one centralized interface with load balancing and circuit breakers.

Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.

A central knowledge hub that connects AI tools to a unified 'Master Brain' with automated memory capabilities. It utilizes intelligent analysis to automatically capture and store key decisions, fixes, and learnings across various development environments.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

Enables AI agents to control monitor settings (brightness, contrast, input source) via DDC/CI protocol, with support for MQTT integration.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with AWS S3 Control API through natural language, auto-generated using AG2's MCP builder.

Start, observe, and interact with Claude Managed Agents from any MCP client — launch an agent, watch its events, reply, approve the tools it wants to run, and stop it. Runs over stdio, HTTP, or AWS Lambda with pluggable auth.

Enables autonomous AI-to-AI collaboration between Claude and Gemini to execute complex development projects with minimal human intervention. It provides a role-based system with task dependencies, automated project planning, and continuous execution loops.

A production-ready MCP server providing comprehensive DevOps capabilities for the Internet Computer blockchain, enabling AI agents to authenticate, manage canisters, handle finances, and build/deploy projects.

Enables programmatic execution of coding tasks and autonomous file operations using Claude AI. It allows agents to search codebases, run shell commands, and track file changes through the Model Context Protocol.

Enables AI to remotely control macOS systems via VNC with full desktop capabilities including screenshots, mouse control, keyboard input, and application management. Includes a web-based chat interface for natural language control.

Connects AI assistants to Obsidian vaults via the Local REST API to search notes, retrieve content, and perform semantic searches. It features self-healing multi-URL connectivity and supports both stdio and HTTP transports for flexible deployment.

Enables conversion of multiple file formats (Markdown, HTML, Word, Excel, etc.) to XMind mind maps with AI-powered analysis for structure optimization and quality assessment.