danielckv/ContextLoom

ContextLoom is the shared "brain" for multi-agent systems. It weaves together memory threads from frameworks like DSPy and CrewAI into a unified, persistent context, powered by Redis and hydrated from your existing databases.

18
/ 100
Experimental

ContextLoom helps developers build sophisticated AI applications where multiple AI agents need to work together and remember past interactions. It takes historical data from your databases (like user profiles or past orders) and ongoing conversations from various AI frameworks, outputting a unified, persistent memory that all agents can share. Developers creating multi-agent systems for customer support, automated research, or complex workflows would use this.

Use this if you are building AI applications with multiple agents that need to share information, avoid repeating themselves, and remember long-term context from your existing databases.

Not ideal if you are working with single-agent AI systems or do not require persistent memory across different AI frameworks or sessions.

AI development multi-agent systems LLM orchestration AI memory management conversational AI
No License No Package No Dependents
Maintenance 6 / 25
Adoption 7 / 25
Maturity 5 / 25
Community 0 / 25

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31

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Language

Python

License

Last pushed

Dec 06, 2025

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