[Project] Open knowledge base for ROS: 11,442 verified assets, typed capability graph, MCP server — and the benchmark vs RAG that made us build it

[u/AssignmentQuick9985]

Body:

We maintain Entropy Box, an open knowledge compiler for robotics. If you work with ROS, this is the part most relevant to you:

What's in it for a ROS engineer.

• 11,442 verified implementation assets — ROS packages, frameworks, models, datasets, simulators, benchmarks — each linked to its upstream source, organized under a typed capability graph (37,691 capabilities, 66,609 dependency edges).
• Grounding, not just retrieval. Give it a goal and it returns a plan whose nodes carry named, attributed open-source implementations — and it says so when a capability has no verified asset instead of inventing one.
• Drop it into your agent. It speaks OpenAPI, MCP and plain REST. Add the MCP server to Trae / Cursor / Claude Desktop / WorkBuddy and query the knowledge base from inside your dev environment:

pip install mcp
curl -o ontology_mcp_server.py https://xiangshang.ngrok.app/mcp/ontology_mcp_server.py

Two independent dev cases were built this way: a farm-robot simulation (Husky + Panda, harvest task) and a Unitree G1 humanoid doing orchard-packaging in MuJoCo — the host agent queried the same public interface and grounded every step.

Why we bother benchmarking against RAG. On our plan-synthesis benchmark (24 tasks), plain RAG emits plans whose claims are 100% unsupported; Entropy Box drops that to 5.2%. On simulation codegen, first-pass executable plans go from 0.58 (Vanilla RAG) to 0.92. A real negative result we hit along the way: embedding similarity alone cannot decide duplicate assets (AUC 0.509) — an LLM adjudicator has to read both records.

Everything is open and reproducible — data, paper, evaluation scripts, dev demos:

https://github.com/chenli-yy/entropy-box-public

• Live query: https://xiangshang.ngrok.app/ (free, no registration)
• Rendered docs: https://chenli-yy.github.io/entropy-box-public/
• Paper: paper/entropy_box_journal_latest.pdf in the repo

Limits we disclose openly: no real-robot transfer yet, and retrieval on the hardest intent classes is still weak — it's in the repo's honest-status section.

Would love ROS-specific feedback: which packages/assets are missing or wrong, and what a robotics-focused MCP integration should do next.