REPOGEO REPORT · LITE

awslabs/mcp

Default branch main · commit 5d56583f · scanned 5/11/2026, 12:57:21 AM

GitHub: 9,015 stars · 1,513 forks

AI VISIBILITY SCORE

40 /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

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 awslabs/mcp, 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

Clarify the Model Context Protocol (MCP) definition in the README's opening

Why:

CURRENT

A suite of specialized MCP servers that help you get the most out of AWS, wherever you use MCP.

COPY-PASTE FIX

A suite of specialized servers implementing the **Model Context Protocol (MCP)**, an open standard for integrating AI agents and large language models (LLMs) with various services. These servers help you get the most out of AWS, wherever you use MCP.

mediumtopics#2

Add more specific AI/agent-related topics

Why:

CURRENT

aws, mcp, mcp-client, mcp-clients, mcp-host, mcp-server, mcp-servers, mcp-tools, modelcontextprotocol

COPY-PASTE FIX

aws, mcp, mcp-client, mcp-clients, mcp-host, mcp-server, mcp-servers, mcp-tools, modelcontextprotocol, ai-agents, llm-integration, generative-ai, agent-toolkit

lowreadme#3

Add a dedicated section clarifying relationship to Agent Toolkit for AWS

Why:

COPY-PASTE FIX

## Relationship to Agent Toolkit for AWS

The Agent Toolkit for AWS is the successor to the MCP servers, plugins, and skills available on AWS Labs, informed by customer feedback. If you're building production software using coding agents or building agents for your own customers, we recommend Agent Toolkit for AWS. This repo continues to work and accept contributions, and over time, the most useful projects here will move into Agent Toolkit for AWS.

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 awslabs/mcp

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

vLLM

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

vLLM · recommended 1×
AWS EC2 (GPU Instances) · recommended 1×
AWS Load Balancer (ALB/NLB) · recommended 1×
Application Load Balancer (ALB) · recommended 1×
Network Load Balancer (NLB) · recommended 1×

CATEGORY QUERY
How can I deploy open source model context protocol servers on AWS infrastructure?
you: not recommended
AI recommended (in order):
1. vLLM
2. AWS EC2 (GPU Instances)
3. AWS Load Balancer (ALB/NLB)
4. Application Load Balancer (ALB)
5. Network Load Balancer (NLB)
6. NVIDIA drivers
7. CUDA
8. Deep Learning AMI
9. Uvicorn
10. Auto Scaling Group (ASG)
11. Amazon S3
12. Amazon EFS
13. TGI (Text Generation Inference)
14. AWS SageMaker Endpoints
15. llama.cpp
16. Kubernetes (EKS)
17. KServe
18. NVIDIA device plugins
19. Horizontal Pod Autoscalers (HPAs)
20. Ingress Controller
21. AWS Load Balancer Controller
22. Amazon CloudWatch
23. AWS IAM roles
24. Amazon FSx for Lustre
AI recommended 24 alternatives but never named awslabs/mcp. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for tools to integrate model context protocol agents with AWS services effectively.
you: not recommended
AI recommended (in order):
1. AWS Lambda
2. Python Boto3 (boto/boto3)
3. AWS Step Functions
4. Amazon API Gateway
5. AWS AppSync
6. AWS Fargate
7. Docker (moby/moby)
8. Amazon Kinesis Data Streams
9. Amazon Kinesis Firehose
AI recommended 9 alternatives but never named awslabs/mcp. 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 awslabs/mcp?
pass
AI named awslabs/mcp explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts awslabs/mcp in production, what risks or prerequisites should they evaluate first?
pass
AI named awslabs/mcp 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 awslabs/mcp solve, and who is the primary audience?
pass
AI named awslabs/mcp explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/awslabs/mcp"><img src="https://repogeo.com/badge/awslabs/mcp.svg" alt="RepoGEO" /></a>

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite