RRepoGEO

REPOGEO REPORT · LITE

QuantGeekDev/mcp-framework

Default branch main · commit ead9c4bb · scanned 5/29/2026, 3:06:57 AM

GitHub: 918 stars · 107 forks

AI VISIBILITY SCORE
27 /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
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 QuantGeekDev/mcp-framework, 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 H1 to clarify 'MCP' and target audience

    Why:

    CURRENT
    # MCP Framework

MCP-Framework is a framework for building Model Context Protocol (MCP) servers elegantly in TypeScript.
    COPY-PASTE FIX
    # MCP Framework: Build Model Context Protocol (MCP) Servers for AI Assistants in TypeScript

MCP-Framework is a robust TypeScript framework designed for building Model Context Protocol (MCP) servers, enabling AI assistants to integrate external tools, resources, and prompts seamlessly.
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    anthropic, claude, framework, genai, llm, llms, mcp, modelcontextprotocol, typescript
    COPY-PASTE FIX
    ai-assistants, model-context-protocol, mcp-framework, llm-tools, typescript, genai, anthropic, claude, server-framework, api-gateway
  • mediumcomparison#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Unlike general-purpose backend frameworks (e.g., NestJS, Fastify) or broad LLM SDKs (e.g., LangChain.js, LlamaIndex.TS), MCP-Framework is purpose-built for creating Model Context Protocol (MCP) servers. It provides out-of-the-box architecture, automatic discovery for tools/resources/prompts, and robust authentication specifically tailored for integrating AI assistants with external capabilities, rather than just interacting with LLMs or building generic APIs.

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 QuantGeekDev/mcp-framework
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NestJS
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NestJS · recommended 1×
  2. TypeORM · recommended 1×
  3. Mongoose · recommended 1×
  4. Next.js · recommended 1×
  5. Fastify · recommended 1×
  • CATEGORY QUERY
    How to build a robust TypeScript backend for AI assistants integrating external tools?
    you: not recommended
    AI recommended (in order):
    1. NestJS
    2. TypeORM
    3. Mongoose
    4. Next.js
    5. Fastify
    6. Express.js
    7. ts-node
    8. Koa.js

    AI recommended 8 alternatives but never named QuantGeekDev/mcp-framework. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Frameworks for defining LLM tools and resources with streaming and authentication in TypeScript?
    you: not recommended
    AI recommended (in order):
    1. LangChain.js (langchain-ai/langchainjs)
    2. LlamaIndex.TS (run-llama/llama_index_ts)
    3. OpenAI SDK (TypeScript) (openai/openai-node)
    4. Hugging Face Transformers.js (huggingface/transformers.js)
    5. NestJS (nestjs/nest)

    AI recommended 5 alternatives but never named QuantGeekDev/mcp-framework. 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 QuantGeekDev/mcp-framework?
    pass
    AI did not name QuantGeekDev/mcp-framework — 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 QuantGeekDev/mcp-framework in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name QuantGeekDev/mcp-framework — 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 QuantGeekDev/mcp-framework solve, and who is the primary audience?
    pass
    AI named QuantGeekDev/mcp-framework explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
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