RRepoGEO

REPOGEO REPORT · LITE

ThinkInAIXYZ/go-mcp

Default branch main · commit 2139a0f9 · scanned 6/5/2026, 6:12:00 AM

GitHub: 669 stars · 107 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 ThinkInAIXYZ/go-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
  • highreadme#1
    Reposition the README overview to clarify 'Model Context Protocol'

    Why:

    CURRENT
    Go-MCP is a powerful Go version of the MCP SDK that implements the Model Context Protocol (MCP) to facilitate seamless communication between external systems and AI applications.
    COPY-PASTE FIX
    Go-MCP is a powerful Go SDK that implements the **Model Context Protocol (MCP)**, a specialized standard designed for seamless, structured data exchange between external systems and AI applications. Unlike generic communication protocols, MCP focuses on managing and transmitting contextual information crucial for AI model interactions, ensuring consistent and relevant data flow.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    golang, go, sdk, ai, artificial-intelligence, protocol, model-context, mcp, context-management, data-exchange
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    [Insert official project homepage URL here, e.g., https://thinkinai.xyz/go-mcp]

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 ThinkInAIXYZ/go-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
gRPC
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. gRPC · recommended 2×
  2. Apache Kafka · recommended 2×
  3. Google Cloud AI Platform · recommended 1×
  4. Vertex AI · recommended 1×
  5. OpenAI Go Library · recommended 1×
  • CATEGORY QUERY
    How to integrate Go applications with AI models for seamless contextual data exchange?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud AI Platform
    2. Vertex AI
    3. OpenAI Go Library
    4. OpenAI
    5. GPT
    6. DALL-E
    7. Whisper
    8. gRPC
    9. TensorFlow Serving
    10. TorchServe
    11. net/http
    12. encoding/json
    13. Apache Kafka
    14. RabbitMQ
    15. Redis
    16. ONNX Runtime
    17. ONNX

    AI recommended 17 alternatives but never named ThinkInAIXYZ/go-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Go libraries for implementing standardized communication protocols with AI applications?
    you: not recommended
    AI recommended (in order):
    1. gRPC
    2. NATS.io (nats-io/nats.go)
    3. Apache Kafka
    4. segmentio/kafka-go (segmentio/kafka-go)
    5. confluentinc/confluent-kafka-go (confluentinc/confluent-kafka-go)
    6. MQTT
    7. eclipse/paho.mqtt.golang (eclipse/paho.mqtt.golang)
    8. WebSocket
    9. gorilla/websocket (gorilla/websocket)
    10. HTTP/2
    11. net/http package

    AI recommended 11 alternatives but never named ThinkInAIXYZ/go-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 ThinkInAIXYZ/go-mcp?
    pass
    AI named ThinkInAIXYZ/go-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 ThinkInAIXYZ/go-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name ThinkInAIXYZ/go-mcp — 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?

  • In one sentence, what problem does the repo ThinkInAIXYZ/go-mcp solve, and who is the primary audience?
    pass
    AI named ThinkInAIXYZ/go-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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ThinkInAIXYZ/go-mcp — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite