RRepoGEO

REPOGEO REPORT · LITE

CopilotKit/open-mcp-client

Default branch main · commit c8ea97b2 · scanned 5/16/2026, 8:38:04 PM

GitHub: 1,639 stars · 249 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 CopilotKit/open-mcp-client, 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
  • highabout#1
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    A client-side library for integrating interactive, context-aware AI copilot functionalities into web applications, part of the CopilotKit ecosystem.
  • hightopics#2
    Add relevant topics to improve discoverability

    Why:

    COPY-PASTE FIX
    ['ai-copilot', 'llm-agent', 'frontend', 'typescript', 'react', 'nextjs', 'full-stack-ai', 'copilotkit']
  • highreadme#3
    Reposition README opening to clarify purpose and CopilotKit connection

    Why:

    CURRENT
    # Open MCP Client

https://github.com/user-attachments/assets/364b6705-14d4-4e6d-bea7-fb9f12664fab

# Getting Started
    COPY-PASTE FIX
    # Open MCP Client

This repository provides the client-side library for integrating interactive, context-aware AI copilot functionalities into web applications, forming a key part of the CopilotKit ecosystem. It enables developers to embed AI agents that understand application state and perform actions directly within the UI. 

https://github.com/user-attachments/assets/364b6705-14d4-4e6d-bea7-fb9f12664fab

# Getting Started

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 CopilotKit/open-mcp-client
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Streamlit
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Streamlit · recommended 2×
  2. LangChain · recommended 2×
  3. Gradio · recommended 2×
  4. Next.js · recommended 2×
  5. FastAPI · recommended 2×
  • CATEGORY QUERY
    How to quickly start building a full-stack AI agent application with a web interface?
    you: not recommended
    AI recommended (in order):
    1. Streamlit
    2. OpenAI API
    3. LangChain
    4. Gradio
    5. Next.js
    6. React
    7. FastAPI
    8. LlamaIndex
    9. Panel
    10. Flask
    11. Django
    12. HTMX

    AI recommended 12 alternatives but never named CopilotKit/open-mcp-client. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good examples of a frontend and Python backend for an LLM-driven agent?
    you: not recommended
    AI recommended (in order):
    1. Next.js
    2. FastAPI
    3. LangChain
    4. SvelteKit
    5. Flask
    6. LlamaIndex
    7. Vue.js
    8. Nuxt.js
    9. Django REST Framework
    10. Haystack
    11. Streamlit
    12. OpenAI
    13. Anthropic
    14. Google Gemini
    15. Gradio

    AI recommended 15 alternatives but never named CopilotKit/open-mcp-client. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    Suggestion:

  • 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 CopilotKit/open-mcp-client?
    pass
    AI did not name CopilotKit/open-mcp-client — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts CopilotKit/open-mcp-client in production, what risks or prerequisites should they evaluate first?
    pass
    AI named CopilotKit/open-mcp-client 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 CopilotKit/open-mcp-client solve, and who is the primary audience?
    pass
    AI named CopilotKit/open-mcp-client explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of CopilotKit/open-mcp-client. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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CopilotKit/open-mcp-client — 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