RRepoGEO

REPOGEO REPORT · LITE

agentic-community/mcp-gateway-registry

Default branch main · commit b0fcb2db · scanned 6/6/2026, 8:21:15 PM

GitHub: 679 stars · 183 forks

AI VISIBILITY SCORE
33 /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
2 / 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 agentic-community/mcp-gateway-registry, 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 the README's opening paragraph to clarify its specialized role for AI agent tool management

    Why:

    CURRENT
    What is MCP Gateway & Registry? The MCP Gateway & Registry is a unified platform designed for centralizing access to both MCP Servers and AI Agents using the Model Context Protocol (MCP). It serves three core functions: 1. Unified MCP Server Gateway – Centralized access point for multiple MCP servers 2. MCP Servers Registry – Register, discover, and manage access to MCP servers with unified governance 3. Agent Registry & A2A Communica
    COPY-PASTE FIX
    The **MCP Gateway & Registry** is an enterprise-ready platform specifically designed to centralize and govern access to AI development tools for autonomous AI agents and AI coding assistants. It transforms scattered AI tool server chaos into a unified, secure, and auditable environment, offering dynamic tool discovery and OAuth authentication (Keycloak/Entra). Unlike general cloud platforms or orchestration tools, it provides a dedicated registry and gateway for the Model Context Protocol (MCP), enabling seamless management and discovery of AI agent skills and tools.
  • mediumtopics#2
    Add more specific AI agent and tool management topics

    Why:

    CURRENT
    a2a, agentic-ai, agents, ans, documentdb, ecs, ecs-fargate, entra-id, fgac, mcp, mcp-gateway, mcp-registry, mcp-servers, mongodb, oauth2, okta, registry, skills, terraform
    COPY-PASTE FIX
    a2a, agentic-ai, agents, ans, documentdb, ecs, ecs-fargate, entra-id, fgac, mcp, mcp-gateway, mcp-registry, mcp-servers, mongodb, oauth2, okta, registry, skills, terraform, ai-agent-orchestration, ai-tool-management, agent-skill-discovery, ai-governance, api-gateway-for-ai
  • lowcomparison#3
    Add a comparison section to the README or documentation

    Why:

    COPY-PASTE FIX
    Add a new section to the README or link to a dedicated `COMPARISON.md` that outlines 'Why MCP Gateway & Registry?' or 'How it Compares' to generic API gateways, cloud ML platforms (like SageMaker/Vertex AI), or general orchestration tools (like Kubernetes) in the context of AI agent tool management.

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 agentic-community/mcp-gateway-registry
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Kubernetes
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Kubernetes · recommended 2×
  2. Azure Machine Learning · recommended 1×
  3. Google Cloud Vertex AI · recommended 1×
  4. AWS SageMaker · recommended 1×
  5. Hugging Face Spaces · recommended 1×
  • CATEGORY QUERY
    How can I centralize access to various AI development tools for agents securely?
    you: not recommended
    AI recommended (in order):
    1. Azure Machine Learning
    2. Google Cloud Vertex AI
    3. AWS SageMaker
    4. Hugging Face Spaces
    5. Hugging Face Inference Endpoints
    6. MLflow
    7. Databricks
    8. Kubernetes
    9. NGINX Ingress Controller
    10. Kong
    11. Domino Data Lab
    12. Pachyderm

    AI recommended 12 alternatives but never named agentic-community/mcp-gateway-registry. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's the best way to manage and discover AI agent skills across many servers?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes
    2. Istio
    3. Linkerd
    4. Apache Kafka
    5. PostgreSQL
    6. MongoDB
    7. Consul
    8. Apache ZooKeeper
    9. Apache Curator
    10. Eureka
    11. Ribbon
    12. Spring Cloud

    AI recommended 12 alternatives but never named agentic-community/mcp-gateway-registry. 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 agentic-community/mcp-gateway-registry?
    pass
    AI did not name agentic-community/mcp-gateway-registry — 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 agentic-community/mcp-gateway-registry in production, what risks or prerequisites should they evaluate first?
    pass
    AI named agentic-community/mcp-gateway-registry 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 agentic-community/mcp-gateway-registry solve, and who is the primary audience?
    pass
    AI named agentic-community/mcp-gateway-registry explicitly

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

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agentic-community/mcp-gateway-registry — 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