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Framework-agnostic agent memory system — Postgres + pgvector + MCP

Project description

ilma

Framework-agnostic agent memory system.

Postgres + pgvector backend. MCP-native. Hermes Agent, Claude, Cursor, Codex — any MCP client.

pip install ilma
ilma init
ilma status

What ilma is

ilma stores what your agents know — and makes it retrievable across sessions, frameworks, and machines.

  • 8 memory surfaces: memories, wiki, journal, skills, metrics, kanban, observability, sessions
  • Hybrid retrieval: vector + FTS + chunk-level reranking
  • MCP server: ilma-mcp — works with any MCP client
  • HTTP API: REST endpoints behind your own reverse proxy
  • CLI: ilma init, ilma search, ilma remember, ilma doctor
  • Postgres + pgvector: proven, backup-friendly, multi-client

Quick start

# Install
pip install ilma

# Initialize (9-step wizard: Postgres, extensions, schemas, embedder)
ilma init

# Store a memory
ilma remember "User prefers dark mode" --tags user,preference

# Search
ilma search "dark mode preference"

# Check health
ilma doctor

Architecture

MCP client (Claude, Cursor, Hermes, etc.)
    ↓  stdio / HTTP
ilma MCP server / HTTP API
    ↓  psycopg3
Postgres + pgvector
    ├─ ilma.memories
    ├─ ilma.wiki
    ├─ ilma.journal
    ├─ ilma.skills
    ├─ ilma.metrics
    ├─ ilma.kanban
    ├─ ilma.observability
    └─ ilma.sessions

Project status

In active development. See PLAN.md for the execution roadmap.

Development

Install dev dependencies and set up pre-commit:

make install
pip install pre-commit
pre-commit install

Run all checks locally:

make all

License

MIT

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