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datamcp Agent Memory

Hosted MCP memory for structured shared project context, controlled writes, and handoffs.

AI & ML

datamcp Agent Memory is a community MCP server that connects AI assistants like Claude to hosted mcp memory for structured shared project context, controlled writes, and handoffs. It runs locally on your machine, keeping your data private and giving you full control over the connection. AI engineers can use it to chain models and pipelines into more powerful workflows.

About datamcp Agent Memory

datamcp Agent Memory provides a remote HTTPS Model Context Protocol connection for structured shared project context across compatible AI clients. It supports project namespaces, project-scoped links, Read Only, Read & Append, and Full Access modes, structured work-log entries, PostgreSQL full-text search and filters, durable structured Markdown compaction, compact handoff context, and reviewed updates to canonical Rules and Project Summary. Connected clients must call the memory tools explicitly. It is not semantic or vector memory, automatic conversation capture, direct file synchronization, or a self-hosted package.

Who Should Use datamcp Agent Memory?

  • 1Chain AI models and pipelines through a unified MCP interface
  • 2Let Claude orchestrate other AI tools and models
  • 3Integrate embeddings, image generation, or speech APIs into your workflow
  • 4Build multi-model workflows without writing custom integration code

How datamcp Agent Memory Compares

It runs entirely on your local machine, so no data leaves your environment — important for teams with privacy or compliance requirements.
Compared to other AI & ML MCP servers, it focuses on a well-scoped set of capabilities, which keeps the integration lightweight and predictable.

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