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How to share project knowledge across a team on one server with AI Memory

Point the whole team at one AI Memory server so each person's agents can retrieve shared project notes.

Credentials. Each team member gets a personal MCP API key, so revoke keys for people who leave the team.

Who it is forA team lead running a small shared codebase who wants every developer's agent to learn from the same project knowledge.

The problemEach developer's agent learns in isolation, so the same architecture and failed approaches are rediscovered by each person.

The outcomeProject knowledge is shared per project, while personal handoffs stay personal, and each person's activity is attributed in an audit log.

What you need first

  • A Linux or macOS machine (native Windows is experimental; WSL2 is supported)
  • At least one supported coding agent CLI installed, such as Claude Code or Codex
  • A terminal with curl and sh available

Steps

  1. Run curl -fsSL https://github.com/akitaonrails/ai-memory/releases/latest/download/install.sh | sh on the server host
  2. Run ai-memory setup on the server host
  3. Have each team member run ai-memory setup on their own machine and connect to the shared server
  4. Use the management console, built with the management-ui feature and started with --enable-management-ui, to create personal MCP API keys for each person (inferred, check the README)

Prompt for your agent

Using the ai-memory repo (github.com/akitaonrails/ai-memory), set up a shared memory server for <team-name> and create one personal key per member. Expected output: each member's agent can search the shared project pages. Verify by searching for a known project fact from a second member's account.

Caveat. The README says the management console needs a compile-time feature and a runtime flag, and the exact build and start commands are only partly shown, so read docs/management-ui.md before deploying.

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