RRepoGEO

REPOGEO REPORT · LITE

obot-platform/obot

Default branch main · commit 6481cbe5 · scanned 6/2/2026, 12:31:29 AM

GitHub: 804 stars · 167 forks

AI VISIBILITY SCORE
33 /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
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 obot-platform/obot, 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 paragraph to clarify platform scope

    Why:

    CURRENT
    Obot is an open-source platform that provides everything an organization needs to implement MCP technologies. It enables you to host MCP servers for internal and external users, set up MCP registries, manage and monitor MCP usage, and build feature-rich agents and chatbots that leverage MCP servers.
    COPY-PASTE FIX
    Obot is a complete, open-source platform for deploying, managing, and monitoring AI agents and large language model (LLM) applications. Unlike frameworks that focus solely on building conversational AI, Obot provides the full infrastructure: hosting, registry, gateway, and a chat client, enabling organizations to implement Model Context Protocol (MCP) technologies with ease.
  • mediumreadme#2
    Add a 'Key Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Differentiators

Obot stands out as a comprehensive, self-hosted platform specifically designed for the Model Context Protocol (MCP). Unlike individual LLM frameworks or MLOps tools, Obot integrates hosting, registry, gateway, and a chat client into a single, unified solution, providing a complete ecosystem for deploying, managing, and monitoring AI agents and LLM applications.
  • lowtopics#3
    Expand GitHub Topics with more specific platform and LLM management terms

    Why:

    CURRENT
    ai, chat, mcp, modelcontextprotocol
    COPY-PASTE FIX
    ai, chat, mcp, modelcontextprotocol, llm-platform, llm-ops, conversational-ai, agent-hosting, self-hosted

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 obot-platform/obot
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Rasa Open Source
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Rasa Open Source · recommended 1×
  2. Botpress · recommended 1×
  3. Open Assistant · recommended 1×
  4. deepset/haystack · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    Seeking an open-source platform to host, manage, and monitor AI agents and chatbots.
    you: not recommended
    AI recommended (in order):
    1. Rasa Open Source
    2. Botpress
    3. Open Assistant
    4. Haystack (deepset/haystack)
    5. LangChain
    6. Apache Superset
    7. Prometheus
    8. Grafana

    AI recommended 8 alternatives but never named obot-platform/obot. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a comprehensive self-hosted solution for deploying and connecting large language model applications.
    you: not recommended
    AI recommended (in order):
    1. OpenShift AI
    2. Kubeflow
    3. Hugging Face TGI (Text Generation Inference)
    4. MLflow
    5. FastAPI
    6. Gradio
    7. Ray Serve
    8. NVIDIA Triton Inference Server

    AI recommended 8 alternatives but never named obot-platform/obot. 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 obot-platform/obot?
    pass
    AI did not name obot-platform/obot — 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 obot-platform/obot in production, what risks or prerequisites should they evaluate first?
    pass
    AI named obot-platform/obot 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 obot-platform/obot solve, and who is the primary audience?
    pass
    AI named obot-platform/obot explicitly

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

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