RRepoGEO

REPOGEO REPORT · LITE

obot-platform/nanobot

Default branch main · commit 6e9489ee · scanned 6/30/2026, 1:41:59 PM

GitHub: 1,326 stars · 200 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
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 obot-platform/nanobot, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Clarify Nanobot's core purpose in the README's opening

    Why:

    CURRENT
    Nanobot enables building agents with MCP and MCP-UI by providing a flexible MCP host.
    COPY-PASTE FIX
    Nanobot is an open-source framework for building and hosting custom AI chatbot agents using the MCP protocol, designed to be a standalone alternative to integrated LLM platforms.
  • lowcomparison#2
    Add a comparison section to differentiate from general LLM frameworks

    Why:

    COPY-PASTE FIX
    ## Nanobot vs. General LLM Frameworks

Unlike broader LLM orchestration frameworks such as LangChain or LlamaIndex, Nanobot is specifically designed as an open-source host for agents built with the MCP (Multi-Agent Communication Protocol) and MCP-UI. While those frameworks provide tools for building various LLM applications, Nanobot focuses on providing a dedicated, deployable environment for MCP-powered conversational AI agents, offering a more opinionated and integrated solution for this specific protocol.

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/nanobot
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Haystack
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Haystack · recommended 2×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. OpenAI Assistants API · recommended 1×
  5. Microsoft Semantic Kernel · recommended 1×
  • CATEGORY QUERY
    How can I create my own custom AI chatbot agent with integrated LLM capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Assistants API
    5. Microsoft Semantic Kernel
    6. AutoGPT
    7. BabyAGI

    AI recommended 7 alternatives but never named obot-platform/nanobot. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source framework to host and deploy custom conversational AI agents.
    you: not recommended
    AI recommended (in order):
    1. Rasa Open Source
    2. DeepPavlov
    3. Open Assistant
    4. ParlAI
    5. Haystack
    6. Botpress

    AI recommended 6 alternatives but never named obot-platform/nanobot. 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 obot-platform/nanobot?
    pass
    AI named obot-platform/nanobot explicitly

    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/nanobot in production, what risks or prerequisites should they evaluate first?
    pass
    AI named obot-platform/nanobot 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/nanobot solve, and who is the primary audience?
    pass
    AI named obot-platform/nanobot explicitly

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

Embed your GEO score

Drop this badge into the README of obot-platform/nanobot. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/obot-platform/nanobot.svg)](https://repogeo.com/en/r/obot-platform/nanobot)
HTML
<a href="https://repogeo.com/en/r/obot-platform/nanobot"><img src="https://repogeo.com/badge/obot-platform/nanobot.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

obot-platform/nanobot — 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