RRepoGEO

REPOGEO REPORT · LITE

NicholasGoh/fastapi-mcp-langgraph-template

Default branch main · commit 2bd004a5 · scanned 6/1/2026, 8:52:58 PM

GitHub: 546 stars · 80 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 NicholasGoh/fastapi-mcp-langgraph-template, 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 and opening sentence to highlight integrated monitoring

    Why:

    CURRENT
    # FastAPI MCP LangGraph Template

A modern template for agentic orchestration — built for rapid iteration and scalable deployment using highly customizable, community-supported tools like MCP, LangGraph, and more.
    COPY-PASTE FIX
    # FastAPI MCP LangGraph Template: Agentic Orchestration with Integrated Monitoring

A modern template for agentic orchestration, built for rapid iteration and scalable deployment, featuring integrated monitoring and observability with tools like MCP, LangGraph, Langfuse, Prometheus, and Grafana.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://mseep.ai/app/nicholasgoh-fastapi-mcp-langgraph-template
  • mediumtopics#3
    Expand repository topics to include solution-oriented keywords

    Why:

    CURRENT
    compose, fastapi, grafana, langfuse, langgraph-python, mcp, nginx, prometheus, sqlmodel, supabase
    COPY-PASTE FIX
    agentic-ai, multi-agent-system, llm-ops, agent-orchestration, fastapi-template, langgraph-template, observability-stack, compose, fastapi, grafana, langfuse, langgraph-python, mcp, nginx, prometheus, sqlmodel, supabase

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 NicholasGoh/fastapi-mcp-langgraph-template
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. run-llama/llama_index · recommended 2×
  3. deepset-ai/haystack · recommended 2×
  4. prometheus/prometheus · recommended 2×
  5. grafana/grafana · recommended 2×
  • CATEGORY QUERY
    How to build a scalable agentic AI application with a modern Python web framework?
    you: not recommended
    AI recommended (in order):
    1. FastAPI (tiangolo/fastapi)
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. Ray (ray-project/ray)
    5. Dask (dask/dask)
    6. CrewAI (joaomdmoura/crewai)
    7. AutoGen (microsoft/autogen)
    8. Django (django/django)
    9. Celery (celery/celery)
    10. Redis (redis/redis)
    11. Haystack (deepset-ai/haystack)
    12. Flask (pallets/flask)

    AI recommended 12 alternatives but never named NicholasGoh/fastapi-mcp-langgraph-template. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a template for orchestrating AI agents with integrated monitoring and observability.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LangSmith
    3. LlamaIndex (run-llama/llama_index)
    4. LlamaCloud
    5. LlamaParse
    6. Haystack (deepset-ai/haystack)
    7. Deepset Cloud
    8. OpenAI Assistants API
    9. Datadog
    10. New Relic
    11. Prometheus (prometheus/prometheus)
    12. Grafana (grafana/grafana)
    13. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    14. Azure Monitor
    15. Application Insights
    16. CrewAI (joaomdmoura/crewAI)
    17. OpenTelemetry (open-telemetry/opentelemetry-specification)
    18. Prometheus (prometheus/prometheus)
    19. Grafana (grafana/grafana)
    20. ELK Stack
    21. Splunk

    AI recommended 21 alternatives but never named NicholasGoh/fastapi-mcp-langgraph-template. 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 NicholasGoh/fastapi-mcp-langgraph-template?
    pass
    AI did not name NicholasGoh/fastapi-mcp-langgraph-template — 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 NicholasGoh/fastapi-mcp-langgraph-template in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NicholasGoh/fastapi-mcp-langgraph-template 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 NicholasGoh/fastapi-mcp-langgraph-template solve, and who is the primary audience?
    pass
    AI did not name NicholasGoh/fastapi-mcp-langgraph-template — 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?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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