balajivis/sutra-mas

36,299 multi-agent systems papers collected, 17,969 analyzed with coordination patterns, embeddings, and a 16-cluster taxonomy — the largest structured MAS corpus bridging 30 years of classical research with modern LLM agents

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Emerging

This project offers a comprehensive database of multi-agent systems research, spanning 30 years from classical concepts to modern LLM agents. It takes a vast collection of academic papers and provides structured insights like coordination patterns, theoretical mappings, and a 16-cluster taxonomy. Researchers, engineers, or anyone building complex AI systems can use this to design more reliable and effective multi-agent solutions by leveraging established coordination protocols.

Use this if you are developing or researching multi-agent AI systems and need to understand proven coordination mechanisms to prevent common failures and improve system reliability.

Not ideal if you are looking for an off-the-shelf software library for building LLM agents without needing to delve into underlying research and coordination theory.

AI Systems Design Agent Coordination LLM Engineering Distributed AI Academic Research
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 11 / 25
Community 14 / 25

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Stars

23

Forks

4

Language

Python

License

Apache-2.0

Last pushed

Feb 16, 2026

Commits (30d)

0

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