RRepoGEO

REPOGEO REPORT · LITE

grafana/mcp-grafana

Default branch main · commit 6e200719 · scanned 5/16/2026, 5:47:16 AM

GitHub: 3,010 stars · 357 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 grafana/mcp-grafana, 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 README H1 and opening paragraph for AI integration

    Why:

    CURRENT
    # Grafana MCP server

A [Model Context Protocol][mcp] (MCP) server for Grafana.

This provides access to your Grafana instance and the surrounding ecosystem.
    COPY-PASTE FIX
    # Grafana MCP Server: AI Integration for Observability

A [Model Context Protocol][mcp] (MCP) server designed to integrate AI assistants (like Claude Desktop or Cursor) with your Grafana instance and its surrounding ecosystem, enabling programmatic access and automated operations.
  • hightopics#2
    Add relevant topics for AI integration and Grafana

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    grafana, ai-integration, observability, model-context-protocol, mcp, plugin, server, automation
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://archestra.ai/mcp-catalog/grafana__mcp-grafana

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 grafana/mcp-grafana
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Datadog
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Datadog · recommended 2×
  2. New Relic · recommended 2×
  3. Splunk · recommended 2×
  4. Grafana · recommended 1×
  5. Terraform · recommended 1×
  • CATEGORY QUERY
    What tools provide programmatic access for managing monitoring dashboards and data sources?
    you: not recommended
    AI recommended (in order):
    1. Grafana
    2. Terraform
    3. Prometheus
    4. Datadog
    5. New Relic
    6. Splunk
    7. Azure Monitor

    AI recommended 7 alternatives but never named grafana/mcp-grafana. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate AI assistants with my observability platform for automated operations?
    you: not recommended
    AI recommended (in order):
    1. Datadog
    2. Watchdog
    3. PagerDuty
    4. ServiceNow
    5. OpenAI's GPT-4
    6. Google's Gemini
    7. Splunk
    8. Splunk IT Service Intelligence (ITSI)
    9. Splunk Machine Learning Toolkit (MLTK)
    10. Splunk SOAR
    11. Dynatrace
    12. Davis AI
    13. Ansible (ansible/ansible)
    14. Jenkins (jenkinsci/jenkins)
    15. New Relic
    16. New Relic Applied Intelligence (NRAI)
    17. Grafana (grafana/grafana)
    18. Prometheus (prometheus/prometheus)
    19. Mimir (grafana/mimir)
    20. Cortex (cortexproject/cortex)
    21. TensorFlow (tensorflow/tensorflow)
    22. PyTorch (pytorch/pytorch)
    23. AWS SageMaker
    24. Google AI Platform
    25. Rundeck (rundeck/rundeck)
    26. StackStorm (StackStorm/st2)
    27. PagerDuty Process Automation
    28. OpenAI
    29. Google AI

    AI recommended 29 alternatives but never named grafana/mcp-grafana. 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 grafana/mcp-grafana?
    pass
    AI named grafana/mcp-grafana explicitly

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

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

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

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