openexp

by anthroos · Python · ★ 58

Outsource your understanding. Capture every human-AI decision as a step in a trajectory; grade trajectories retroactively when outcomes land (deal closed, sprint shipped). Hooks + MCP server for Claude Code, Qdrant + FastEmbed local-first.

#ai-agents#claude#claude-code#decision-extraction#episodic-memory#experience-packs#llm-tools#mcp#memory#outcome-grading#qdrant#trajectory

Install

pip install git+https://github.com/anthroos/openexp.git

Auto-generated from the repo's primary language — check the repo's own README for its exact install instructions.

Claude Desktop config

A starting point for your claude_desktop_config.json (auto-generated — the repo's README may specify a published package name or required env vars):

{
  "mcpServers": {
    "openexp": {
      "command": "uvx",
      "args": [
        "git+https://github.com/anthroos/openexp.git"
      ]
    }
  }
}

From the README

OpenExp How did this happen? — a hippocampus for AI agents. Capture trajectories raw. Grade only when reality returns its verdict. Build a labeled corpus of human-AI decisions tied to grounded outcomes. Quick Start · How It Works · Pipeline · Publish · MCP Tools · Status When you close a deal, ship a feature, or lose a client — *how did it happen*? Which decisions, in what order, against which context, on which hypotheses? Today's AI agents can't answer that. They follow skills and instructions perfectly, but they d…

Read full README on GitHub →

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