REPOGEO REPORT · LITE

robotmcp/ros-mcp-server

Default branch main · commit 91fa6664 · scanned 5/14/2026, 2:52:59 PM

GitHub: 1,220 stars · 182 forks

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface robotmcp/ros-mcp-server, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Clarify README's opening to explicitly define MCP and state the project's core category

Why:

CURRENT

ROS-MCP-Server connects large language models (such as Claude, GPT, and Gemini) to robots, enabling bidirectional communication with no changes to existing robot source code.

COPY-PASTE FIX

ROS-MCP-Server (Model Context Protocol) connects large language models (such as Claude, GPT, and Gemini) to robots, enabling bidirectional communication with no changes to existing robot source code. This project is a core component for AI-powered robotics, specifically for LLM-robot integration.

hightopics#2

Add more specific keywords to the topics list

Why:

CURRENT

mcp, mcp-server, modelcontextprotocol, ros, ros-mcp-server, ros2, ros2-mcp-server

COPY-PASTE FIX

mcp, mcp-server, modelcontextprotocol, ros, ros-mcp-server, ros2, ros2-mcp-server, llm-robotics, ai-robotics, robot-control, natural-language-robotics, generative-ai-robotics

mediumreadme#3

Add a dedicated 'Core Differentiators' section to the README

Why:

COPY-PASTE FIX

## Core Differentiators

ROS-MCP-Server stands out by:
- **Enabling LLM-Robot Control without Code Changes:** Connects large language models to robots by simply adding a `rosbridge` node, requiring no modifications to existing robot source code.
- **True Bidirectional LLM Communication:** Allows LLMs to both control robots and observe real-time sensor data and robot state.
- **Deep ROS Integration:** Guides LLMs to discover and correctly use ROS topics, services, actions, and parameters, including custom types.
- **Open Standard Compatibility:** Built on the open Model Context Protocol (MCP), supporting various LLM clients like Claude Code, Gemini CLI, and ChatGPT.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface robotmcp/ros-mcp-server

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

ROS

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

ROS · recommended 1×
Python · recommended 1×
OpenAI API · recommended 1×
Hugging Face Transformers · recommended 1×
RT-1 · recommended 1×

CATEGORY QUERY
How to integrate large language models for robot control and real-time observation?
you: not recommended
AI recommended (in order):
1. ROS
2. Python
3. OpenAI API
4. Hugging Face Transformers
5. RT-1
6. RT-2
7. LangChain
8. NVIDIA Isaac Sim
9. Omniverse ACE
10. Microsoft Semantic Kernel
11. Llama 2
12. Mistral
13. Falcon
14. ONNX Runtime
15. TensorRT
AI recommended 15 alternatives but never named robotmcp/ros-mcp-server. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a ROS tool for bidirectional LLM communication with minimal robot code changes.
you: not recommended
AI recommended (in order):
1. ROS 2 AI (or ROS-AI)
2. ros_llm
3. ros_openai
4. ros_huggingface
5. requests library
6. ROS 2 Web Bridge (ros2_web_bridge)
AI recommended 6 alternatives but never named robotmcp/ros-mcp-server. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of robotmcp/ros-mcp-server?
pass
AI named robotmcp/ros-mcp-server explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts robotmcp/ros-mcp-server in production, what risks or prerequisites should they evaluate first?
pass
AI named robotmcp/ros-mcp-server explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo robotmcp/ros-mcp-server solve, and who is the primary audience?
pass
AI named robotmcp/ros-mcp-server explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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robotmcp/ros-mcp-server — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite