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How to self-host a long-term memory server for your agents with Deepmem

Run the open-mode server with Qdrant so agents can store and recall facts per user_id.

Short answer: Clone the repo and copy the example env file to .env; then configure your LLM provider in .env; start the stack and call the memories endpoint. All steps.

Who it is forA developer who cannot send user conversations to a third-party memory service.

The problemAgents forget users between sessions without a memory store.

The outcomeA private memory API with hybrid retrieval and per-user isolation.

What you need first

  • Python
  • Docker for self-hosting with Qdrant, or a DeepMem Cloud key
  • An LLM provider for fact extraction

Steps

  1. Clone the repo and copy the example env file to .env
  2. Configure your LLM provider in .env
  3. Start the stack and call the memories endpoint
  4. Search memories for a test user_id

Prompt for your agent

Self-host deepmemteam/deepmem, store a message for user <id>, then search for a fact from it. Confirm the result is scoped to that user_id only.

Caveat. Open mode has no API key or user registration, so do not expose the server to the internet without your own auth in front.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for deepmemteam/deepmem and "Self-host a long-term memory server for your agents"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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