I Built a MCP Server for Robot Operating System

Hacker News

I've been experimenting with ROS (Robot Operating System) and the Model Context Protocol (MCP), and noticed a gap: while there were some MCP servers for ROS, most were limited. They either only supported topic communication or had hard-coded topic names, which severely limited their reusability. To address this, I built a general-purpose MCP server for ROS that allows interaction with ROS topics, services, and actions -making it more flexible and extensible than previous approaches. A key design decision was enabling communication between the MCP server and a local ROS machine by simply exporting the ROS_DOMAIN_ID via the claude_desktop_config.json file. This small trick made it possible to bridge the gap between local nodes and the MCP server. Github: https://github.com/Yutarop/ros-mcp Would love feedback or suggestions!

Visit product View on Hacker NewsJun 19, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, claude, model · Missing: agents, macos, agent

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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