RRepoGEO

REPOGEO REPORT · LITE

SalesforceAIResearch/MCP-Universe

Default branch main · commit 1861b366 · scanned 6/3/2026, 6:21:50 AM

GitHub: 588 stars · 84 forks

AI VISIBILITY SCORE
28 /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
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 SalesforceAIResearch/MCP-Universe, 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

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

OVERALL DIRECTION
  • mediumreadme#1
    Strengthen README's opening statement to emphasize benchmarking for tool-use agents

    Why:

    CURRENT
    MCP-Universe is a comprehensive ecosystem for building, optimizing, and evaluating AI agents that interact with the Model Context Protocol (MCP).
    COPY-PASTE FIX
    MCP-Universe is a comprehensive framework for RL training, benchmarking, and developing AI agents for general tool-use, specifically designed to evaluate LLMs in real-world scenarios through interaction with actual Model Context Protocol (MCP) servers.
  • lowreadme#2
    Explicitly state the unique differentiator in the README

    Why:

    COPY-PASTE FIX
    Unlike existing benchmarks, MCP-Universe uniquely focuses on evaluating the multimodal chain-of-thought (CoT) reasoning process of large language models, providing human-annotated CoTs across diverse modalities.

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 SalesforceAIResearch/MCP-Universe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. AutoGen · recommended 1×
  5. CrewAI · recommended 1×
  • CATEGORY QUERY
    How can I build and evaluate AI agents that use various external tools effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. CrewAI
    6. OpenAI Assistants API
    7. Guidance

    AI recommended 7 alternatives but never named SalesforceAIResearch/MCP-Universe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks exist for training and benchmarking AI agents on complex real-world tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym / Gymnasium
    2. RLlib
    3. Stable Baselines3
    4. DeepMind Lab
    5. Unity ML-Agents Toolkit
    6. MetaWorld
    7. Procgen Benchmark

    AI recommended 7 alternatives but never named SalesforceAIResearch/MCP-Universe. 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 SalesforceAIResearch/MCP-Universe?
    pass
    AI did not name SalesforceAIResearch/MCP-Universe — 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 SalesforceAIResearch/MCP-Universe in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SalesforceAIResearch/MCP-Universe 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 SalesforceAIResearch/MCP-Universe solve, and who is the primary audience?
    pass
    AI named SalesforceAIResearch/MCP-Universe 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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  • Brand-free category queries5 vs 2 in Lite
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