memsearch is a markdown-first memory system designed to provide long-term memory capabilities for AI agents through structured storage and semantic retrieval. It enables agents to store, organize, and retrieve information using embeddings and hybrid search techniques, ensuring that relevant context is always available. The system supports advanced features such as reranking and progressive disclosure, which help prioritize the most useful information for a given query. It integrates with vector databases like Milvus, enabling scalable storage and retrieval of large datasets. Memsearch is designed to be agent-friendly, making it easy to plug into existing AI workflows and enhance reasoning capabilities. Its markdown-first approach ensures transparency and portability of stored knowledge. Overall, it provides a robust foundation for building AI systems with persistent and intelligent memory.

Features

  • Markdown-first storage for AI memory
  • Semantic search with embeddings
  • Integration with vector databases like Milvus
  • Reranking for improved retrieval accuracy
  • Progressive disclosure of relevant information
  • Designed for agent-based workflows

Project Samples

Project Activity

See All Activity >

Categories

Agent Skills

License

MIT License

Follow memsearch

memsearch Web Site

Other Useful Business Software
Go from Code to Production URL in Seconds Icon
Go from Code to Production URL in Seconds

Cloud Run deploys apps in any language instantly. Scales to zero. Pay only when code runs.

Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
Try it free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of memsearch!

Additional Project Details

Programming Language

Python

Related Categories

Python Agent Skills

Registered

2026-04-23