Anamnese: A Portable Memory Layer for Claude and ChatGPT via MCP
Anamnese is a free MCP server that addresses a common pain point when using multiple AI assistants: the lack of persistent, portable memory. The developer built it after finding that context about themselves, their projects, and their working style didn't carry over between sessions with Claude and ChatGPT.
Key Details
The tool stores four types of information:
- Memories
- Tasks
- Goals
- Notes
It has been in personal use for about two months, with the developer noting it "remembers the tiniest details and never gets full."
One key design consideration: Anamnese doesn't dump your entire memory into the context window. Instead, it only pulls what's relevant to the current conversation, keeping interactions clean and focused.
Users maintain full ownership and control over their data. You can:
- View your stored information
- Edit entries
- Delete content
- Export data whenever you want
The tool works with Claude, ChatGPT, and any MCP client. It's available at https://anamneseai.app/.
The developer specifically mentions that native memory features in AI assistants "help a bit" but have limitations: you can't really see what the AI knows, can't edit the stored information, and the memory eventually fills up.
This type of tool is useful for developers who regularly work with multiple AI assistants and want consistent context across sessions without retyping background information each time.
📖 Read the full source: r/ClaudeAI
👀 See Also
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antirez's DS4: Running DeepSeek V4 Flash with 1M Context on Mac Metal and DGX
Redis creator Salvatore Sanfilippo released DS4, a project to run DeepSeek V4 Flash with a 1M context window on Mac Metal hardware and DGX, with OpenAI/Anthropic endpoints for agentic coding tools.
AutoAgents Rust Framework Adds Python Bindings for Prototyping
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repo-mem: Open-Source MCP Server Adds Persistent Team Memory to Claude Code
repo-mem is an open-source MCP server that adds persistent, shared memory to Claude Code sessions using SQLite and Git. It solves team isolation by storing observations in per-user databases that get committed to the repository.