AI Visibility Checker
Server Details
Check if ChatGPT, Perplexity & Google AI recommend a brand, plus an AI-agent readiness audit. Free.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.9/5 across 2 of 2 tools scored.
Both tools have clearly distinct purposes: one checks website technical readiness for AI crawlers, the other checks brand visibility in AI recommendations. No overlap.
Both tools follow a consistent 'check_' prefix naming pattern, making them easy to identify and predict.
Only 2 tools for a domain that could logically include more (e.g., monitoring, reporting). While they cover core features, the set feels minimal.
Covers two key aspects of AI visibility (readiness and brand mentions), but lacks tools for ongoing monitoring, competitor comparison, or detailed analytics. Notable gaps exist.
Available Tools
2 toolscheck_agent_readinessCheck Agent ReadinessARead-onlyInspect
Audit whether a website is ready for AI shopping/research AGENTS to discover and use it: AI-crawler access (GPTBot/ClaudeBot/PerplexityBot), llms.txt, schema.org structured data, and a /.well-known agent manifest. Returns a 0-100 agent-readiness score with specific gaps. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Website URL to audit (https://...). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, openWorldHint, destructiveHint) cover safety. The description adds value by listing specific checks and return format (score with gaps), and mentions it is free, which is behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is three sentences, front-loaded with purpose. It efficiently communicates the core function and output. Minor room for tighter phrasing but overall well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description adequately explains what it returns (score, specific gaps). Complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full description for the single 'url' parameter (including 'https://...'). The description does not add meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool audits website readiness for AI agents, listing specific checks (AI-crawler access, llms.txt, schema.org, agent manifest) and outputs a 0-100 score with gaps. It distinguishes itself from sibling 'check_ai_visibility' by focusing on agent readiness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The sibling tool 'check_ai_visibility' exists but no differentiation is provided. 'Free' hints at accessibility but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_ai_visibilityCheck AI VisibilityARead-onlyInspect
Check whether AI assistants (ChatGPT, Perplexity, Google AI Overviews) recommend a brand when buyers ask for recommendations in its category. Returns an AI Visibility Score (0-100), how often the brand is named across real buyer questions, and which competitor brands the AI names instead. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Optional website URL to improve the audit. | |
| brand | Yes | Brand or company name to check. | |
| market | No | Optional market: us, uk, jp, kr, de, fr, es, br, in. Default us. | |
| category | Yes | Category buyers ask AI about, e.g. 'project management software'. |
Output Schema
| Name | Required | Description |
|---|---|---|
| brand | No | |
| score | No | AI Visibility Score 0-100 |
| total | No | |
| market | No | |
| category | No | |
| mentions | No | |
| reportUrl | No | |
| competitors | No | Brands AI names instead |
| mentionRate | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, openWorldHint) already indicate safety and read-only nature. The description adds valuable behavioral context: it returns an AI Visibility Score (0-100), frequency of brand mentions, competitor brands, and notes it is free. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) and front-loaded with purpose. It could be better structured (e.g., brief bullet points) but is clear and avoids fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and an output schema, the description adequately covers core function, return values (score, frequency, competitors), and cost. It is sufficient for an agent to understand the tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minor context (e.g., URL is optional, market defaults to us) but does not provide semantic meaning beyond what the parameter descriptions already convey. No additional parameter explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action (check), the resource (AI visibility), and the scope (AI assistants like ChatGPT, Perplexity, Google AI Overviews). It distinguishes from the sibling tool 'check_agent_readiness' by focusing on brand recommendations in buyer queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use the tool (to check AI recommendations for a brand in a category) and implies it is free, but does not explicitly mention when not to use it or provide alternatives beyond the sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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