RRepoGEO

REPOGEO REPORT · LITE

rinadelph/Agent-MCP

Default branch main · commit 13d98b2c · scanned 5/11/2026, 3:47:11 PM

GitHub: 1,233 stars · 162 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 rinadelph/Agent-MCP, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    multi-agent-systems, ai-agents, agent-orchestration, ai-collaboration, model-context-protocol, python, fastapi
  • mediumhomepage#2
    Set a homepage URL for the repository

    Why:

    COPY-PASTE FIX
    https://deepwiki.com/rinadelph/Agent-MCP
  • lowreadme#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a section like '## License' to your README, stating: 'This project is licensed under [Name of your custom/compound license(s) as found in the LICENSE file]. Please refer to the LICENSE file for full details.'

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 rinadelph/Agent-MCP
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AutoGen
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. AutoGen · recommended 2×
  2. CrewAI · recommended 2×
  3. LangChain · recommended 2×
  4. Haystack · recommended 2×
  5. LlamaIndex · recommended 2×
  • CATEGORY QUERY
    How to build a system for multiple AI agents to collaborate efficiently on development tasks?
    you: not recommended
    AI recommended (in order):
    1. AutoGen
    2. CrewAI
    3. LangChain
    4. Haystack
    5. LlamaIndex
    6. Open Interpreter
    7. BabyAGI
    8. Auto-GPT

    AI recommended 8 alternatives but never named rinadelph/Agent-MCP. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Advanced framework for orchestrating parallel AI agents with shared context and task management?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Haystack
    3. LlamaIndex
    4. AutoGen
    5. CrewAI
    6. Marvin

    AI recommended 6 alternatives but never named rinadelph/Agent-MCP. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 rinadelph/Agent-MCP?
    pass
    AI named rinadelph/Agent-MCP explicitly

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

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

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

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rinadelph/Agent-MCP — 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
rinadelph/Agent-MCP — RepoGEO report