RRepoGEO

REPOGEO REPORT · LITE

pathintegral-institute/mcpm.sh

Default branch main · commit 6a92e54c · scanned 6/11/2026, 5:52:03 PM

GitHub: 968 stars · 106 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 pathintegral-institute/mcpm.sh, 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 'MCP' in the README's opening statement

    Why:

    CURRENT
    MCPM is an open source CLI tool for managing MCP servers. It provides a simplified global configuration approach where you install servers once and organize them with profiles, then integrate them into any MCP client. Features include server discovery through a central registry, direct execution, sharing capabilities, and client integration tools.
    COPY-PASTE FIX
    MCPM is an open source CLI tool for managing **AI Model Context Protocol (MCP) servers**. It provides a simplified global configuration approach where you install servers once and organize them with profiles, then integrate them into any MCP client. Features include server discovery through a central registry, direct execution, sharing capabilities, and client integration tools.
  • hightopics#2
    Refine topics to be more specific to AI model context management

    Why:

    CURRENT
    ai, claude-desktop, cli, cline, continue, cursor, goose, homebrew, llm, mcp, package-manager, pip, profile, routing, sse, stdio, tools, windsurf
    COPY-PASTE FIX
    ai, llm, model-context, mcp-protocol, cli-tool, server-management, ai-development, claude-desktop, package-manager, routing, profile
  • mediumabout#3
    Explicitly mention 'AI' in the repository description

    Why:

    CURRENT
    CLI MCP package manager & registry for all platforms and all clients. Search & configure MCP servers. Advanced Router & Profile features.
    COPY-PASTE FIX
    CLI **AI Model Context Protocol (MCP)** package manager & registry for all platforms and clients. Search & configure **AI** MCP servers. Advanced Router & Profile features.

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 pathintegral-institute/mcpm.sh
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
kubernetes/kubernetes
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. kubernetes/kubernetes · recommended 1×
  2. kubeflow/kubeflow · recommended 1×
  3. OpenShift AI · recommended 1×
  4. mlflow/mlflow · recommended 1×
  5. Hugging Face Inference Endpoints · recommended 1×
  • CATEGORY QUERY
    How can I manage multiple AI model context servers and their configurations globally?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes (kubernetes/kubernetes)
    2. KubeFlow (kubeflow/kubeflow)
    3. OpenShift AI
    4. MLflow (mlflow/mlflow)
    5. Hugging Face Inference Endpoints
    6. Text Generation Inference (huggingface/text-generation-inference)
    7. AWS SageMaker
    8. Azure Machine Learning
    9. Google Cloud Vertex AI
    10. HashiCorp Nomad (hashicorp/nomad)
    11. Consul (hashicorp/consul)
    12. Vault (hashicorp/vault)
    13. Docker Compose (docker/compose)
    14. NGINX (nginx/nginx)
    15. Caddy (caddyserver/caddy)
    16. Ansible (ansible/ansible)
    17. SaltStack (saltstack/salt)

    AI recommended 17 alternatives but never named pathintegral-institute/mcpm.sh. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What command-line tools exist for installing and configuring AI development environments or services?
    you: not recommended
    AI recommended (in order):
    1. Conda
    2. Docker
    3. pip
    4. Poetry
    5. NVIDIA Container Toolkit
    6. Kubernetes
    7. AWS CLI
    8. Azure CLI
    9. gcloud CLI

    AI recommended 9 alternatives but never named pathintegral-institute/mcpm.sh. 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 pathintegral-institute/mcpm.sh?
    pass
    AI named pathintegral-institute/mcpm.sh explicitly

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

  • If a team adopts pathintegral-institute/mcpm.sh in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pathintegral-institute/mcpm.sh 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 pathintegral-institute/mcpm.sh solve, and who is the primary audience?
    pass
    AI named pathintegral-institute/mcpm.sh explicitly

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

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pathintegral-institute/mcpm.sh — RepoGEO report