REPOGEO REPORT · LITE

stacklok/toolhive

Default branch main · commit 8fd704ea · scanned 5/12/2026, 9:56:57 PM

GitHub: 1,790 stars · 217 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 stacklok/toolhive, 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 opening to clarify unique domain and differentiate from miscategorizations

Why:

CURRENT

ToolHive runs every MCP server in an isolated container, enforces identity and access policy per request, and gives platform teams the observability they need to put MCP in production.

COPY-PASTE FIX

ToolHive is the enterprise-grade platform for securely running and managing Model Context Protocol (MCP) servers, distinct from general security tool orchestration or CI/CD runner solutions. It runs every MCP server in an isolated container, enforces identity and access policy per request, and gives platform teams the observability they need to put MCP in production.

mediumreadme#2

Add a concise explanation of Model Context Protocol (MCP) to the README

Why:

COPY-PASTE FIX

## What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is a standard for securely exchanging context between AI code assistants and external tools. ToolHive provides the essential platform to host, secure, and manage these critical MCP servers, ensuring enterprise-grade control over your AI interactions.

lowtopics#3

Expand repository topics with more specific AI infrastructure terms

Why:

CURRENT

ai, ai-security, aicodeassistant, golang, kubernetes, mcp, mcp-security, mcp-servers, mcp-tools, model-context-protocol, security

COPY-PASTE FIX

ai, ai-security, aicodeassistant, golang, kubernetes, mcp, mcp-security, mcp-servers, mcp-tools, model-context-protocol, security, ai-platform, llm-ops, ai-infrastructure, model-serving

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 stacklok/toolhive

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

istio/istio

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

istio/istio · recommended 1×
linkerd/linkerd2 · recommended 1×
hashicorp/vault · recommended 1×
Kubernetes Secrets · recommended 1×
external-secrets/external-secrets · recommended 1×

CATEGORY QUERY
How to securely deploy and manage AI model context servers on Kubernetes infrastructure?
you: not recommended
AI recommended (in order):
1. Istio (istio/istio)
2. Linkerd (linkerd/linkerd2)
3. HashiCorp Vault (hashicorp/vault)
4. Kubernetes Secrets
5. External Secrets Operator (external-secrets/external-secrets)
AI recommended 5 alternatives but never named stacklok/toolhive. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are options for self-hosting and securing AI code assistant backends for enterprise use?
you: not recommended
AI recommended (in order):
1. GitHub Enterprise Server
2. GitHub Copilot Enterprise
3. GitLab Self-Managed
4. GitLab Duo Code Suggestions
5. OpenAI API
6. Azure OpenAI Service
7. Hugging Face Inference Endpoints
8. text-generation-inference
9. optimum
10. Code Llama
11. StarCoder
AI recommended 11 alternatives but never named stacklok/toolhive. 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 stacklok/toolhive?
pass
AI named stacklok/toolhive explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts stacklok/toolhive in production, what risks or prerequisites should they evaluate first?
pass
AI named stacklok/toolhive 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 stacklok/toolhive solve, and who is the primary audience?
pass
AI did not name stacklok/toolhive — 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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MARKDOWN (README)

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HTML

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

Pro

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stacklok/toolhive — 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