RRepoGEO

REPOGEO REPORT · LITE

datagouv/datagouv-mcp

Default branch main · commit b381cfd8 · scanned 6/24/2026, 3:47:40 AM

GitHub: 1,545 stars · 126 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /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
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 datagouv/datagouv-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 H1 to specify its category for AI

    Why:

    CURRENT
    # data.gouv.fr MCP Server
    COPY-PASTE FIX
    # AI Chatbot Integration Server for data.gouv.fr Open Data (MCP)
  • mediumtopics#2
    Expand repository topics to include broader AI and data interaction terms

    Why:

    CURRENT
    mcp, mcp-server, open-data, opendata
    COPY-PASTE FIX
    mcp, mcp-server, open-data, opendata, ai-chatbot, chatbot-integration, natural-language-processing, nlp, government-data, public-data, data-analysis-ai, llm-integration
  • lowcomparison#3
    Add a 'Why Choose This?' section to the README to differentiate from generic tools

    Why:

    COPY-PASTE FIX
    ## Why Choose datagouv-mcp?

Unlike general-purpose LLM frameworks (e.g., LangChain, LlamaIndex) or BI tools (e.g., PowerBI Copilot), `datagouv-mcp` is a specialized, ready-to-use server specifically designed to provide AI chatbots with direct, conversational access to the rich, structured datasets of data.gouv.fr. It handles the complexities of data.gouv.fr's API and metadata, allowing developers to integrate AI assistants with French open government data without building custom connectors.

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 datagouv/datagouv-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Amazon Lex · recommended 2×
  4. Dataherald · recommended 1×
  5. PowerBI Copilot · recommended 1×
  • CATEGORY QUERY
    How to enable AI chatbots to interactively analyze public datasets through natural language?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Dataherald
    4. PowerBI Copilot
    5. Tableau Ask Data
    6. Streamlit
    7. Gradio
    8. Google Dialogflow
    9. Amazon Lex

    AI recommended 9 alternatives but never named datagouv/datagouv-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to make open government data explorable by AI assistants conversationally.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vertex AI
    2. Google Cloud BigQuery
    3. Google Cloud Knowledge Graph
    4. Vertex AI Workbench
    5. Vertex AI Notebooks
    6. Google Cloud Vertex AI Conversation
    7. Dialogflow CX
    8. Microsoft Azure Cognitive Services
    9. Azure OpenAI Service
    10. Azure SQL Database
    11. Azure Cosmos DB
    12. Azure Cognitive Search
    13. GPT-4
    14. GPT-3.5 Turbo
    15. Microsoft Bot Framework
    16. Neo4j AuraDB
    17. Neo4j
    18. LangChain
    19. OpenAI API
    20. Amazon Web Services (AWS)
    21. Amazon S3
    22. Amazon RDS
    23. Amazon DynamoDB
    24. Amazon Neptune
    25. Amazon Kendra
    26. Amazon Lex
    27. Amazon Bedrock
    28. Anthropic Claude
    29. AI21 Labs Jurassic
    30. Amazon Titan
    31. DataStax Astra DB
    32. Apache Cassandra
    33. RAGStack
    34. LlamaIndex

    AI recommended 34 alternatives but never named datagouv/datagouv-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
    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 datagouv/datagouv-mcp?
    pass
    AI named datagouv/datagouv-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 datagouv/datagouv-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named datagouv/datagouv-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 datagouv/datagouv-mcp solve, and who is the primary audience?
    pass
    AI named datagouv/datagouv-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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datagouv/datagouv-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