RRepoGEO

REPOGEO REPORT · LITE

TensorBlock/awesome-mcp-servers

Default branch main · commit a4a89f95 · scanned 6/5/2026, 10:27:47 AM

GitHub: 727 stars · 462 forks

AI VISIBILITY SCORE
27 /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
1 / 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 TensorBlock/awesome-mcp-servers, 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
    Immediately clarify 'MCP' in the README's opening sentence

    Why:

    CURRENT
    A comprehensive, community-curated collection of Model Context Protocol (MCP) servers — covering AI assistants, browser automation, databases, cloud platforms, developer tools, and much more.
    COPY-PASTE FIX
    A comprehensive, community-curated collection of **Model Context Protocol (MCP) servers for AI models** — covering AI assistants, browser automation, databases, cloud platforms, developer tools, and much more.
  • hightopics#2
    Add more explicit AI-related topics to reinforce the domain

    Why:

    CURRENT
    anthropic, awesome, genai, mcp, mcp-server, mcp-server-discovery, mcp-servers, model-context-protocol
    COPY-PASTE FIX
    anthropic, awesome, genai, mcp, mcp-server, mcp-server-discovery, mcp-servers, model-context-protocol, ai-models, ai-tools, ai-integration, context-management
  • mediumreadme#3
    Elevate the 'What is MCP?' definition for immediate clarity

    Why:

    CURRENT
    > **What is MCP?** The Model Context Protocol is an open standard that lets AI models securely connect to external tools, APIs, databases, and filesystems. Think of it as a USB-C port for AI — a universal interface that any model can use to interact with the world.
    COPY-PASTE FIX
    **What is MCP?** The Model Context Protocol is an open standard that lets AI models securely connect to external tools, APIs, databases, and filesystems. Think of it as a USB-C port for AI — a universal interface that any model can use to interact with the world.

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 TensorBlock/awesome-mcp-servers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Vertex AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Vertex AI · recommended 2×
  2. OpenAI API · recommended 1×
  3. Azure OpenAI Service · recommended 1×
  4. Anthropic API · recommended 1×
  5. Hugging Face Inference API · recommended 1×
  • CATEGORY QUERY
    How to find and compare different AI model providers supporting a common context protocol?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Azure OpenAI Service
    3. Google Cloud Vertex AI
    4. Anthropic API
    5. Hugging Face Inference API
    6. transformers library (huggingface/transformers)
    7. Anyscale Endpoints
    8. Together AI

    AI recommended 8 alternatives but never named TensorBlock/awesome-mcp-servers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help manage context and integrate various AI models from different providers?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Assistants API
    4. Microsoft Azure AI Studio
    5. Google Cloud Vertex AI
    6. Haystack
    7. Zapier
    8. Make

    AI recommended 8 alternatives but never named TensorBlock/awesome-mcp-servers. 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 TensorBlock/awesome-mcp-servers?
    pass
    AI did not name TensorBlock/awesome-mcp-servers — 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 TensorBlock/awesome-mcp-servers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TensorBlock/awesome-mcp-servers 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 TensorBlock/awesome-mcp-servers solve, and who is the primary audience?
    pass
    AI did not name TensorBlock/awesome-mcp-servers — 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?

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TensorBlock/awesome-mcp-servers — RepoGEO report