RRepoGEO

REPOGEO REPORT · LITE

lastmile-ai/mcp-agent

Default branch main · commit f62d8493 · scanned 5/25/2026, 7:36:17 PM

GitHub: 8,337 stars · 845 forks

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 lastmile-ai/mcp-agent, 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 opening to explicitly state it's a Python LLM agent framework

    Why:

    CURRENT
    Build effective agents with Model Context Protocol using simple, composable patterns.
    COPY-PASTE FIX
    A Python framework for building robust LLM-powered agents using the Model Context Protocol and simple, composable patterns.
  • mediumhomepage#2
    Add homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://docs.mcp-agent.com
  • mediumcomparison#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, '## `mcp-agent` vs. Other LLM Agent Frameworks' or '## Why `mcp-agent`?' that clearly outlines its unique value proposition, especially in contrast to frameworks like LangChain and LlamaIndex, emphasizing its focus on MCP and simple patterns.

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 lastmile-ai/mcp-agent
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. Haystack · recommended 2×
  4. CrewAI · recommended 2×
  5. AutoGPT · recommended 1×
  • CATEGORY QUERY
    How can I build reliable AI agents with large language models using simple patterns?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. CrewAI
    6. Guidance
    7. Transformers Agents

    AI recommended 7 alternatives but never named lastmile-ai/mcp-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some good Python frameworks for developing robust and composable LLM-powered agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. CrewAI
    5. AutoGen
    6. Marvin

    AI recommended 6 alternatives but never named lastmile-ai/mcp-agent. 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 lastmile-ai/mcp-agent?
    pass
    AI did not name lastmile-ai/mcp-agent — 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 lastmile-ai/mcp-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name lastmile-ai/mcp-agent — 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?

  • In one sentence, what problem does the repo lastmile-ai/mcp-agent solve, and who is the primary audience?
    pass
    AI named lastmile-ai/mcp-agent explicitly

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

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lastmile-ai/mcp-agent — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite