RRepoGEO

REPOGEO REPORT · LITE

bytebase/dbhub

Default branch main · commit 72adfdcf · scanned 5/23/2026, 10:42:55 PM

GitHub: 2,819 stars · 240 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 bytebase/dbhub, 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's opening to emphasize 'AI database management server'

    Why:

    COPY-PASTE FIX
    Add a prominent H1 and opening paragraph to your README, clearly stating: `# DBHub: The Zero-Dependency Server for AI-Powered Database Management` followed by a sentence like: `DBHub acts as a token-efficient, central control plane (MCP) for connecting AI assistants and developer tools to diverse relational databases like Postgres, MySQL, and SQL Server.`
  • mediumtopics#2
    Add more explicit AI-database server integration topics

    Why:

    CURRENT
    agents, ai, anthropic, claude, claude-ai, codex, cursor, database, dify, llm, mariadb, mcp, mcp-server, mssql, mysql, postgres, postgresql, sql, sqlite, sqlserver
    COPY-PASTE FIX
    agents, ai, anthropic, claude, claude-ai, codex, cursor, database, dify, llm, mariadb, mcp, mcp-server, mssql, mysql, postgres, postgresql, sql, sqlite, sqlserver, ai-database-management, llm-database-connector, database-proxy, ai-agent-backend, database-api
  • lowreadme#3
    Highlight DBHub's Git-like model for database schema changes

    Why:

    COPY-PASTE FIX
    Add a dedicated section or a prominent paragraph in the README titled 'Why DBHub is Different' or 'GitOps for Databases', explaining how DBHub applies a Git-like branching, merging, and versioning model directly to database schema changes, differentiating it from traditional migration tools or generic database clients.

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 bytebase/dbhub
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DataGrip
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DataGrip · recommended 1×
  2. EverSQL · recommended 1×
  3. DBmarlin · recommended 1×
  4. ChatGPT · recommended 1×
  5. Google Gemini · recommended 1×
  • CATEGORY QUERY
    How to manage multiple SQL databases like Postgres and MySQL using an AI assistant?
    you: not recommended
    AI recommended (in order):
    1. DataGrip
    2. EverSQL
    3. DBmarlin
    4. ChatGPT
    5. Google Gemini
    6. GitHub Copilot
    7. AWS CodeWhisperer
    8. SQLFlow

    AI recommended 8 alternatives but never named bytebase/dbhub. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a zero-dependency server to centralize management for diverse relational database systems.
    you: not recommended
    AI recommended (in order):
    1. Adminer
    2. DBeaver Community Edition
    3. SQL Operations Studio (Azure Data Studio)
    4. SQuirreL SQL Client
    5. HeidiSQL

    AI recommended 5 alternatives but never named bytebase/dbhub. 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 bytebase/dbhub?
    pass
    AI named bytebase/dbhub explicitly

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

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

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

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