MCP ServerHTTPOfficialv1.0.0

Anamnese MCP Server

Sync your personal notes, tasks, and goals across different AI environments using this self-improving memory layer. This server is designed for developers who need a persistent, context-aware knowledge base that evolves alongside their projects.

app.anamneseai/anamnese

Hosted URL

https://anamneseai.app/api/mcp

Transport

HTTP

Auth

No auth required

What the Anamnese MCP server does

How models use it and what it is built for.

Sync your personal notes, tasks, and goals across different AI environments using this self-improving memory layer. This server is designed for developers who need a persistent, context-aware knowledge base that evolves alongside their projects.

Connect to Anamnese

Hosted endpoint — paste into any MCP client.

https://anamneseai.app/api/mcp

Resources

Where to find authoritative docs and source for Anamnese.

Example prompts for Anamnese

Paste any of these into Agent Studio after connecting Anamnese.

  • Retrieve my current project goals and active tasks from the memory layer.
  • Add a new note about the API authentication flow to my persistent memory.
  • Summarize the key objectives I defined in my notes earlier this week.
  • Explain how to configure the Anamnese MCP server using the provided HTTP endpoint.

Anamnese MCP server — FAQ

Common questions about connecting and running Anamnese.

  • What is the primary function of the Anamnese MCP server?

    The Anamnese MCP server acts as a centralized, self-improving memory layer for your AI agents. It allows you to store and retrieve notes, tasks, and goals across various platforms.

  • How do I connect to the Anamnese MCP server?

    You can connect to the server using the HTTP transport protocol. Simply configure your MCP client to point to the hosted endpoint at https://anamneseai.app/api/mcp.

  • Is the Anamnese memory layer persistent?

    Yes, the server is designed to act as a persistent memory layer. It ensures that your notes and tasks remain accessible across different sessions and AI interactions.

  • Are there specific environment variables required for setup?

    The provided registry data does not explicitly list required environment variables. Please consult the official Anamnese documentation or the connection settings in your MCP client for authentication requirements.

  • How does the self-improving aspect of this memory layer work?

    The server is described as a self-improving memory layer, implying it organizes and refines stored data over time. For specific details on its internal logic, please refer to the official Anamnese developer documentation.

Run Anamnese across 40+ AI models, side-by-side

Connect Anamnese to Claude, GPT, Gemini, DeepSeek and 40+ AI models in MCP Agent Studio. Compare answers side-by-side, save reusable agent presets, share runs — all in your browser, no install required.

Open Agent Studio

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