int

Self-hosted, Dockerized, open-source AI memory system. Exposes a project-scoped memory store to AI coding assistants via the Model Context Protocol (MCP), so assistants can recall prior-session learnings without re-running expensive discovery work.

Status

v1 in progress. Spec at docs/spec.md; intent at docs/intent.md; task breakdown at tasks/todo.md.

Related MCP server: AIVectorMemory

Quick start

cp .env.example .env          # fill in API_KEY and GEMINI_API_KEY
docker compose up -d          # server + Qdrant
docker compose logs -f int    # tail server

Point OpenCode at the server by adding a remote MCP entry to your opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "int": {
      "type": "remote",
      "url": "http://localhost:8000/mcp",
      "headers": { "API_KEY": "{env:API_KEY}" }
    }
  }
}

See docs/deployment.md for full setup, CLI usage, and common pitfalls.

Tools

Tool names are bare (add, search, ...). The MCP server is registered as int, so MCP clients expose them as int_add, int_search, int_list, int_delete.

Stack

Python 3.14, FastAPI + MCP (mcp Python SDK, Streamable HTTP), Qdrant (separate container), gemini-embedding-001 (L2-normalized to 768 dims via MRL), Docker Compose, uv for dep management.

License

Apache-2.0 — see LICENSE for details.