Anemoi: A Semi-Centralized Multi-agent Systems Based on Agent-to-Agent Communication MCP server from Coral Protocol

Anemoi is a semi-centralized multi-agent system (MAS) built on a Agent-to-Agent (A2A) communication MCP server. Unlike traditional context-engineering + centralized paradigms, Anemoi introduces structured, direct inter-agent communication — enabling agents to collaborate much like a real-world team.

🌀 Like winds connecting distant lands, Anemoi enables agents to communicate directly in a semi-centralized network, achieving scalable coordination and seamless information flow.

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🚀 Key Features

• Semi-Centralized Architecture Reduces dependency on a single planner agent, supporting adaptive plan updates.

• Direct Agent-to-Agent Collaboration Agents can monitor progress, assess results, identify bottlenecks, and propose refinements in real time.

• Efficient Context Management Minimizes redundant prompt concatenation and information loss, improving scalability and cost-efficiency.

• Benchmark Performance Achieved 52.73% accuracy on the validation set of the GAIA benchmark, setting the state-of-the-art among small-LLM-based systems.

  Surpasses OWL (43.63%) by +9.09% in the same worker agents and models configuration (gpt-4.1-mini as planner agent/ gpt-4o as worker agent).

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📄 Publication

Our work has been released on arXiv:

👉 Anemoi: A Semi-Centralized Multi-agent Systems Based on Agent-to-Agent Communication MCP server from Coral Protocol

If you find this project useful, please consider citing our paper:

@article{ren2025anemoi,
  title={Anemoi: A Semi-Centralized Multi-agent Systems Based on Agent-to-Agent Communication MCP server from Coral Protocol},
  author={Ren, Xinxing and Forder, Caelum and Zang, Qianbo and Tahir, Ahsen and Georgio, Roman J. and Deb, Suman and Carroll, Peter and Gürcan, Önder and Guo, Zekun},
  journal={arXiv preprint arXiv:2508.17068},
  year={2025},
  url={https://arxiv.org/abs/2508.17068}
}

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🧪 Reproduction

Set up environment variables:

echo '
export FIRECRAWL_API_KEY="your_firecrawl_api_key"
export GOOGLE_API_KEY="your_google_api_key"
export HF_HOME="your_hf_home_path"
export OPENROUTER_API_KEY="your_openrouter_api_key"
export SEARCH_ENGINE_ID="your_search_engine_id"
export CHUNKR_API_KEY="your_chunkr_api_key"
' >> ~/.bashrc && source ~/.bashrc

Create environment:

cd Anemoi
/usr/bin/python3.12 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

We made some minor modifications to CAMEL 0.2.70 for our experiments:

rm -rf venv/lib/python3.12/site-packages/camel
cp -r utils/camel venv/lib/python3.12/site-packages/

Run the experiment:

cd ..
./gradlew run --console=plain