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.
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Openexp is an MCP server that 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. Its tool list has not been published yet over sse, requires no API key, and scores 67/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"openexp": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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Capture trajectories raw. Grade only when reality returns its verdict. Build a labeled corpus of human-AI decisions tied to grounded outcomes.
This server supports HTTP transport. Be the first to test it — help the community know if it works.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
Click any tool to inspect its schema.
anonymizeTakes raw trajectory data and produces an anonymized YAML trajectory with PII replaced by category tokens while preserving structural features
extract_experienceReads anonymized trajectory plus terminal outcome label and produces facts-only meta.yaml with id, outcome label, duration, step count, category tokens, and license
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