Scan websites for AI visibility and marketing health with interactive dashboard.
Scan a competitor and return side-by-side comparison
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| max_pages | No | ||
| competitor_url | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Scan a competitor' suggests some form of web scanning, but there is no disclosure of side effects, permissions, rate limits, or whether the operation is read-only. The impact on the system is unclear.
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 front-loads the primary action. It is efficient, though it sacrifices substance for brevity. It earns its place as a purpose statement, but lacks additional helpful structure.
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?
With three parameters (two required), no output schema, and no annotations, the description is insufficient. It does not clarify the meaning of 'url' vs 'competitor_url', what max_pages controls, or the format of the comparison result. A more complete description would explain these aspects.
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 0%, and the description adds no parameter details. It mentions 'competitor' which relates to competitor_url, but omits the roles of 'url' and 'max_pages'. The description does not compensate for the lack of schema descriptions.
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 scans a competitor and returns a side-by-side comparison, distinguishing it from sibling tools like scan_website which likely scans a single site. The verb and resource are specific, though it could be clearer about what is being compared.
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?
There is no explicit guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, use cases, or alternatives such as scan_website or get_score_breakdown. The description implies a comparison scenario but fails to provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get detailed line-item breakdown for a score dimension
| Name | Required | Description | Default |
|---|---|---|---|
| checks | Yes | ||
| dimension | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It says 'get detailed line-item breakdown,' which implies a read operation, but it does not confirm side effects, authorization requirements, or what a 'line-item' actually consists of. The term 'detailed' is vague and does not explain the return structure or any potential errors.
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 short sentence with no filler, front-loading the core purpose. It is appropriately sized, but given the lack of other context, it could earn its place better by including a bit more detail without becoming verbose.
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?
With no output schema, the description must explain what the tool returns, but it does not. The 'checks' parameter is undefined, and the description does not clarify how the dimension enum affects the breakdown. This is insufficient for an agent to invoke the tool correctly without additional implicit knowledge.
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 has 2 parameters with 0% description coverage. The description mentions 'score dimension,' which maps to the 'dimension' parameter, but it does not explain the 'checks' parameter at all. Given the low schema coverage, the description must compensate for both parameters, and it fails to do so fully.
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 uses a specific verb 'get' and identifies a clear resource: a detailed line-item breakdown for a score dimension. This distinguishes it from sibling tools like compare_scan, refresh_scan, scan_website, and submit_lead, none of which perform a similar breakdown function.
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 is provided on when to use this tool or how it relates to alternatives. There are no mentions of exclusions, prerequisites, or scenarios where this tool should be preferred over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Re-scan with updated parameters
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| max_pages | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'Re-scan with updated parameters' without mentioning side effects, permissions, or what happens to previous results, providing no behavioral context beyond the action itself.
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 sentence without fluff, which is structurally concise. However, its brevity borders on under-specification, offering minimal information relative to what an agent needs to invoke the tool correctly.
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 lack of annotations, no output schema, and minimal parameter descriptions, the description is insufficient for an agent to correctly use the tool. It does not explain the scan process, return values, or edge cases, leaving critical gaps.
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 schema has 0% description coverage, and the description does not explain the url or max_pages parameters. 'Updated parameters' is generic and does not clarify which parameters are involved or their semantic meaning.
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 states 'Re-scan with updated parameters,' which identifies the verb (re-scan) and indicates a repeat scan with new settings. However, it does not specify what is being scanned or how it differs from the sibling tool scan_website, making its purpose somewhat vague.
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 no guidance on when to use this tool versus alternatives. It does not mention scan_website, use cases, exclusions, or prerequisites, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Scan any website for AI visibility and marketing health. Returns scores for GEO (Generative Engine Optimization), Multimodal readiness, Agent-Ready infrastructure, and 6-dimension Marketing Health. Identifies critical findings with prioritized fix recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The website URL to scan (e.g. https://example.com) | |
| industry | No | Industry vertical for context | general |
| max_pages | No | Maximum subpages to scan (default: 5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds that the tool returns scores, findings, and recommendations, but does not disclose behavioral traits such as external API usage, rate limits, or authentication requirements beyond what annotations imply.
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?
Two sentences with no wasted words. The purpose is front-loaded and every sentence provides distinct value: first sentence states action and output categories, second sentence adds findings and recommendations.
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 no output schema, the description explains return values (scores, findings, recommendations) adequately. It covers key output dimensions. However, it does not mention the scanning scope (subpages via max_pages) or any limitations, and the '6-dimension Marketing Health' is left undefined.
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 the baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already provides (URL format, industry context, max pages). It focuses on outputs rather than parameter guidance.
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 scans websites for AI visibility and marketing health, listing specific score categories. However, it does not explicitly differentiate from sibling tools like compare_scan or get_score_breakdown, leaving some ambiguity about when this tool is preferred.
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 says 'Scan any website' but provides no guidance on when to use this tool versus alternatives like compare_scan or refresh_scan. There are no exclusions, prerequisites, or context signals suggesting optimal use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Submit a lead for service booking
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| tier | Yes | ||
| Yes | |||
| company | No | ||
| scan_url | Yes | ||
| findings_count | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only states 'submit,' implying a write/mutation, but omits side effects, idempotency, return values, or required permissions.
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, but it is under-specified for a tool with 6 parameters. It is front-loaded but not appropriately sized.
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 lack of annotations, no output schema, and a complex parameter set, the description is critically incomplete. It fails to convey what happens after submission, result format, or how to interpret required fields.
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 has 6 parameters, but the description adds zero explanation for any of them. It does not clarify the meaning of 'tier,' 'scan_url,' or 'findings_count,' despite schema coverage being 0%.
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 uses a specific verb ('Submit') and names the resource ('lead for service booking'), providing clear scope. It is distinct from sibling tools like scan_website or compare_scan, which are read/analyze operations.
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 is provided on when to use this tool versus alternatives. It does not mention sibling tools, list exclusions, or explain prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
compare_scanget_score_breakdownrefresh_scanscan_websitesubmit_leadClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
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After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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
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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
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The server is experiencing an outage
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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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Scan any public site for AI-agent visibility; get scored findings, a machine-readable fix pack, and
Scan any website's AI readiness: AI search visibility and AI agent usability. Free, no auth.
Scan any website for AI readiness — 100-point score across 6 AEO categories in seconds.
Search indexed websites, read raw page markdown, and score AI visibility for any site.
Add one secure layer between your agents and this server.
Most tools have clear distinct purposes: scanning, comparing, getting breakdowns, and submitting leads. However, refresh_scan and scan_website are similar in action, potentially causing confusion about when to use each, though descriptions provide some clarity.
All tool names follow a consistent verb_noun pattern (compare_scan, get_score_breakdown, refresh_scan, scan_website, submit_lead). This makes the naming predictable and easy to understand.
With 5 tools, the server is well-scoped for its purpose. Each tool serves a distinct function in the workflow, and the count is neither too sparse nor overwhelming.
The core scanning workflow is covered: scan, compare, refresh, and get details. A minor gap is the lack of a tool to list or retrieve a specific scan history, but this is not a critical omission for the apparent purpose.
