🧠 ThinkingCap

A multi-agent research MCP server that runs multiple LLM providers in parallel and synthesizes their responses. Built on the Model Context Protocol for seamless integration with Claude Desktop, Cursor, and other MCP-compatible tools.

🌟 Features

🔀 Multi-Agent Research: Deploy multiple AI agents simultaneously for comprehensive analysis
🎯 Multi-Provider Support: OpenAI, Anthropic, xAI, Google, OpenRouter, Groq, Cerebras
⚡ Parallel Execution: All agents run concurrently for maximum speed
🔄 Intelligent Synthesis: Combines multiple perspectives into unified, comprehensive answers
🔍 Built-in Web Search: DuckDuckGo search integration (no API key required)
🔌 MCP Native: Works with any MCP-compatible client via npx

🚀 Quick Start

Installation

No installation required! Just add to your MCP client configuration.

Configuration

Add the following to your MCP client configuration (e.g., ~/.cursor/mcp.json):

{ "mcpServers": { "thinkingcap": { "command": "npx", "args": [ "-y", "thinkingcap", "openrouter:moonshotai/kimi-k2-thinking", "groq:moonshotai/kimi-k2-instruct-0905", "cerebras:zai-glm-4.6", "xai:grok-4-fast" ] } } }

Customizing Agents

You can specify any combination of providers and models as arguments:

"args": [ "-y", "thinkingcap", "anthropic:claude-sonnet-4-20250514", "openai:gpt-4o", "google:gemini-2.0-flash" ]

📋 Supported Providers

Provider	Env Variable	Default Model	Example
`openai`	`OPENAI_API_KEY`	gpt-5.1	`openai:gpt-4o`
`openrouter`	`OPENROUTER_API_KEY`	moonshotai/kimi-k2-thinking	`openrouter:anthropic/claude-3.5-sonnet`
`groq`	`GROQ_API_KEY`	moonshotai/kimi-k2-instruct-0905	`groq`
`cerebras`	`CEREBRAS_API_KEY`	zai-glm-4.6	`cerebras`
`xai`	`XAI_API_KEY`	grok-4-fast	`xai:grok-4-fast`
`anthropic`	`ANTHROPIC_API_KEY`	claude-opus-4-5	`anthropic`
`google`	`GOOGLE_API_KEY`	gemini-3-pro-preview	`google:gemini-2.0-flash`

🔑 Environment Variables

API keys are read from environment variables. Add them to your ~/.bashrc or ~/.zshrc:

export OPENROUTER_API_KEY="sk-or-..." export GROQ_API_KEY="gsk_..." export CEREBRAS_API_KEY="..." export XAI_API_KEY="..." # etc.

🛠️ How It Works

Query Decomposition: Your research query is broken into multiple specialized questions
Parallel Execution: Each agent (provider/model combo) researches a different angle
Web Search: Each agent performs web searches to gather current information
Synthesis: All agent responses are combined into one comprehensive answer

🔥 OpenRouter Fireworks Routing

When using OpenRouter, requests are automatically routed to Fireworks as the preferred provider with fallbacks enabled for maximum reliability.

📝 License

MIT License

🙏 Acknowledgments

Built on the Model Context Protocol
Inspired by multi-agent AI research systems

This server cannot be installed

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security - not tested

A

license - permissive license

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quality - not tested

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Related Resources

GitHub Repository

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