RRepoGEO

REPOGEO REPORT · LITE

chatmcp/mcp-server-chatsum

Default branch main · commit 5bf9298a · scanned 6/29/2026, 9:22:49 PM

GitHub: 1,029 stars · 101 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
22 /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
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 chatmcp/mcp-server-chatsum, 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's opening to clarify personal chat summarization

    Why:

    CURRENT
    This MCP Server is used to summarize your chat messages.
    COPY-PASTE FIX
    This MCP Server is designed to query and summarize your *personal* chat messages, integrating seamlessly with local AI clients like Claude Desktop. It allows you to analyze your chat history stored in a local database using AI prompts.
  • highlicense#2
    Add a LICENSE file and declare the license

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root directory with the text of the MIT License. Then, add a section to your README, e.g., '## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.'
  • mediumtopics#3
    Add more specific topics for personal AI chat summarization

    Why:

    CURRENT
    chatbot, chatsum, mcp-server
    COPY-PASTE FIX
    personal-ai, chat-summarization, local-ai, claude-desktop, sqlite-database, privacy-focused, llm-application, mcp-server

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 chatmcp/mcp-server-chatsum
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ChatGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ChatGPT · recommended 1×
  2. OpenAI API · recommended 1×
  3. Claude · recommended 1×
  4. Anthropic API · recommended 1×
  5. Google Gemini · recommended 1×
  • CATEGORY QUERY
    How can I automatically summarize my past chat conversations using an AI tool?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT
    2. OpenAI API
    3. Claude
    4. Anthropic API
    5. Google Gemini
    6. Google AI Studio
    7. Gemini API
    8. Notion AI
    9. Zapier
    10. Make
    11. NLTK
    12. SpaCy
    13. Hugging Face Transformers

    AI recommended 13 alternatives but never named chatmcp/mcp-server-chatsum. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to query and analyze my personal chat history database.
    you: not recommended
    AI recommended (in order):
    1. DB Browser for SQLite
    2. DBeaver Community Edition
    3. Jupyter Notebook
    4. Pandas
    5. SQLAlchemy
    6. Metabase
    7. Tableau Public
    8. Power BI Desktop
    9. Google Sheets
    10. Microsoft Excel

    AI recommended 10 alternatives but never named chatmcp/mcp-server-chatsum. 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 chatmcp/mcp-server-chatsum?
    pass
    AI did not name chatmcp/mcp-server-chatsum — 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 chatmcp/mcp-server-chatsum in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chatmcp/mcp-server-chatsum 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 chatmcp/mcp-server-chatsum solve, and who is the primary audience?
    pass
    AI did not name chatmcp/mcp-server-chatsum — 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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chatmcp/mcp-server-chatsum — 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