by anthroos · MCP Server · ★ 43
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 Quick Start That installs the four hooks into Claude Code, brings up Qdrant in Docker, and registers the MCP server. Prerequisites: Python 3.11+, Docker, jq. No API key required for core
| Stars | 43 |
| Forks | 4 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 55.68/100 |
| Open Issues | 4 |
| Last Updated | 2026-05-04 |
| Created | 2026-03-22 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~36k |
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openexp is 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 Claud. It is categorized as a MCP Server with 43 GitHub stars.
openexp is primarily written in Python. It covers topics such as ai-agents, claude, claude-code.
You can find installation instructions and usage details in the openexp GitHub repository at github.com/anthroos/openexp. The project has 43 stars and 4 forks, indicating an active community.
openexp is released under the MIT license, making it free to use and modify according to the license terms.