Solitaire: Open-Source Identity Infrastructure for AI Agents
Solitaire is an open-source identity infrastructure project for AI agents that addresses how agents improve their working relationship with users over time, rather than just focusing on memory recall. The project has been in production since February 2024, with development shaped by 600+ real user sessions.
Key Features
The system emphasizes local-first architecture with:
- All storage using SQLite + JSONL in your workspace directory
- Zero network requests from the core engine
- No cloud dependency, no telemetry, no external API calls for memory operations
- Automatic rolling backups without any setup
- All data stays on your machine
Core Functionality
Solitaire includes several technical components developed through production use:
- Persona and behavioral identity that compiles from real interaction, not static config
- Retrieval weighting that adjusts based on what actually proved useful
- Self-correcting knowledge graph with contradiction detection, confidence rescoring, and entity relinking
- Tiered boot context so the agent arrives briefed, not blank
- Session residues that carry forward how the work felt, not just what was discussed
- Guided onboarding where new users build a partner through conversation, not a JSON file
Installation and Compatibility
Install via: pip install solitaire-ai (note: NOT install solitaire, which is an unrelated package)
The architecture is model-agnostic and currently runs on:
- Claude Code
- Cowork
- Hermes
- OpenClaw
- Gemini CLI
A Dify plugin is in prototype, with work ongoing for Open LLM integration.
Current Status
The system has processed 600+ sessions with 15,700+ entries in real production use. It's available on PyPI and the MCP Registry. Two research papers from the longitudinal work are currently in review.
License: AGPL-3.0, with commercial licensing available for proprietary embedding.
The developer is seeking feedback on top-requested integrations, areas for improvement in the memory layer, and any missed opportunities.
📖 Read the full source: r/LocalLLaMA
👀 See Also
Obsidian Integration for Persistent Memory in OpenClaw and Claude Code
A Reddit user demonstrates how connecting OpenClaw and Claude Code to an Obsidian vault creates persistent long-term memory across sessions. The setup automatically links memories, context, project files, and notes, with all instances able to access shared memory when needed.
Parallel Coding Agents with tmux and Markdown Specs
Manuel Schipper describes a system for running 4-8 parallel coding agents using tmux, Markdown files, bash aliases, and six slash commands. The setup uses Feature Design (FD) Markdown specs tracked through an 8-stage lifecycle.
Engram: Open-source memory layer for Claude Code and MCP clients
Engram is an open-source memory layer that works as an MCP server with any client like Claude Code, Cursor, or Windsurf. It stores unlimited memories with semantic vector search, achieves 80% accuracy on LOCOMO benchmark, and uses about 800 tokens per query versus 5K+ for file-based approaches.
How I built a 3D scroll website in 2 hours using Claude Code and Veo
A developer built a 3D scroll website in 2 hours using Claude Code, Veo video generation, and a custom 'video to website' skill. Full code and live demo shared.