Free AI visibility (GEO/AEO) audit: can ChatGPT, Claude and Perplexity find and cite your website?
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.
Average 4/5 across 2 of 2 tools scored.
The two tools serve clearly distinct purposes: one schedules a strategy call, the other runs an AI visibility audit. There is no overlap or ambiguity in their intended use.
Both tools follow the same verb_noun pattern: 'book_strategy_call' and 'run_ai_visibility_audit'. The naming is consistent and immediately conveys the action and target.
With only 2 tools, the set is slightly under the typical 3-15 range, but it fits the server's narrow, focused purpose of AI visibility auditing and lead generation. The count is reasonable and not excessively thin.
The server covers the core workflow of auditing a website's AI visibility and provides a clear next step for deeper engagement via a strategy call. Minor gaps exist (e.g., no separate tool for report retrieval or status checks), but the instant snapshot and email delivery mitigate these.
book_strategy_callAInspectGet the link to book a free Specularis strategy call about AI visibility / GEO / AEO.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a read-only action ('Get the link') but does not explicitly state side effects, permissions, or that it does not modify anything. The mention of 'free' and 'strategy call' adds context but no behavioral disclosure. Adequate but not rich.
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 a single, concise sentence that directly states the tool's function. It contains no redundant information and is well-structured for quick comprehension.
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?
The tool is very simple (no params, no output schema), and the description provides the essential purpose. It does not describe the return format of the link, but the phrase 'Get the link' implies the output. The description is complete enough for this complexity level, though it lacks any mention of prerequisites or target audience.
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 tool has zero parameters, and schema description coverage is 100% (vacuous). The baseline for 0 params is 4, and the description does not need to explain any parameter semantics. No additional clarity is required.
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's purpose: 'Get the link to book a free Specularis strategy call about AI visibility / GEO / AEO.' It uses a specific verb ('Get the link') and resource ('Specularis strategy call'), and it distinguishes itself from the sibling tool 'run_ai_visibility_audit' by focusing on booking a call rather than running an audit.
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 tells what the tool does but provides no guidance on when to use it versus the sibling tool. It does not mention scenarios like 'if you want to schedule a call' or explicitly exclude cases for the audit tool. This lacks any comparative usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_ai_visibility_auditAInspectRun a free AI visibility (GEO/AEO) audit on a website — checks whether ChatGPT, Claude, and Perplexity can find and cite it. Returns an instant snapshot of crawler access, structured data, and llms.txt. If an email is provided, a full scored report (0–100 across 5 pillars, with copy-paste fixes) is emailed as a PDF. Use this whenever a user asks to audit/check a site's AI visibility, GEO, AEO, or whether AI can find them.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Optional name for the report greeting. | |
| role | No | Optional. Tailors the audit lens — local-service providers are scored on local entity signals, reviews, and directories. | |
| No | Optional. If provided, the full scored PDF report is emailed here (and the user becomes a Specularis lead). Omit for just the instant snapshot. | ||
| website_url | Yes | The website to audit, e.g. https://example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses key behaviors: the audit is free, returns an instant snapshot, sends a full PDF report if email is provided, and generates a lead ('the user becomes a Specularis lead'). It does not disclose all potential edge cases (e.g., invalid URLs), but the major side effects are covered.
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 three sentences, front-loaded with the primary purpose, then output details, then usage guidance. Every sentence earns its place with no redundant 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?
Despite no output schema, the description explains both output modalities (instant snapshot and full PDF report with scoring details). It covers the main behaviors and side effects. Minor gaps remain (e.g., error handling for inaccessible sites), but for a tool of this complexity it is sufficiently complete.
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 description coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the schema for parameters like website_url, name, role, or email; it only restates the email effect (PDF send/lead) which is already in the schema. No additional param-level insight is provided.
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 opens with a specific verb and resource: 'Run a free AI visibility (GEO/AEO) audit on a website' and clearly states the three AI engines checked (ChatGPT, Claude, Perplexity). It also distinguishes itself from the sibling tool (book_strategy_call) by focusing on audit rather than scheduling.
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 provides explicit usage triggers: 'Use this whenever a user asks to audit/check a site's AI visibility, GEO, AEO, or whether AI can find them.' It does not mention when not to use or name alternatives, but the context is clear and sufficient for differentiation from the only 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.
No comments yet. Be the first to start the discussion!
Sign in to create a connector for this server.