Content
# 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.*
<p align="center">
<img src="Anemoi/images/Anemoi_semi.png" alt="Anemoi Concept" width="70%">
</p>
---
## 🚀 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).
<p align="center">
<img src="Anemoi/images/Anemoi_workflow.png" alt="Anemoi Workflow" width="85%">
</p>
---
## 📄 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](https://arxiv.org/abs/2508.17068)
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}
}
```
---
## 🧪 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
```
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