Security, SEO and AI-visibility scanner for web apps · free scans and focused checks via MCP.
AEO check: whether AI answer engines (ChatGPT/GPTBot, Claude, Perplexity, Google-Extended, etc.) can crawl and cite the site, plus llms.txt and structured-data signals.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full https URL to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. Description adds specific crawler list and signal types, providing useful behavioral context without contradiction.
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?
Single sentence, front-loaded with 'AEO check', no wasted words. Efficient and direct.
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?
Simple tool with one param and no output schema. Description covers what is checked (engines, signals) adequately. Slightly lacking on output format but acceptable given simplicity.
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% with url parameter fully described. Description adds no additional parameter meaning beyond schema, meeting baseline expectation.
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?
Description clearly states the tool checks AI answer engine visibility, specifying exact engines (ChatGPT, Claude, etc.) and signals (llms.txt, structured-data). Distinct from sibling tools that focus on security, email, SEO, etc.
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?
Context is clear via 'AEO check' and specific engines listed, but no explicit when-not-to-use or alternatives mentioned. Implied usage is appropriate for AI crawler audits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check a domain's email authentication: SPF, DKIM (common selectors), and DMARC policy. Flags spoofable domains.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain, e.g. example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and openWorldHint. Description adds specific details about checking common DKIM selectors and flagging spoofable domains, which goes beyond annotations. No contradictions.
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?
Single sentence, front-loaded with purpose, no redundant words. Efficiently conveys what the tool does.
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, description hints at output by mentioning 'flags spoofable domains.' For a simple tool, it is mostly complete. Could elaborate on the format of results.
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 covers 100% of parameters with description for domain. Description adds no further parameter-specific semantics beyond the schema's example.
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?
Description clearly states the tool checks SPF, DKIM, and DMARC for a domain and flags spoofable domains. It distinguishes from siblings which cover other security aspects like SSL, headers, etc.
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 explicit when-to-use or when-not-to-use guidance. Context from siblings implies use for email authentication, but lacks explicit alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Probe a site for accidentally exposed high-risk files (.env, .git/config, backups, etc.). Reports HTTP status only, never file contents.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full https URL to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds critical context: 'Reports HTTP status only, never file contents.' This clarifies the non-destructive, status-only behavior 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?
Two sentences with no waste. The first sentence fronts the action and scope, the second clarifies limitation. Every word earns its place.
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 single-parameter tool with no output schema, the description is sufficiently complete: it explains what it does, what it returns (HTTP status), and what it avoids (file contents). Annotations cover safety. Minor gap: no mention of rate limits or expected HTTP status codes.
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% (parameter 'url' described as 'Full https URL to check'). The description adds no additional parameter meaning beyond the schema, warranting the baseline score.
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 ('Probe') and resource ('exposed high-risk files') with concrete examples (.env, .git/config, backups). It clearly distinguishes from sibling tools like check_ssl or check_email_security by focusing on file exposure detection.
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 does not explicitly state when to use this tool versus alternatives. It implies usage for security audits but lacks guidance on conditions (e.g., after initial site discovery) or when to prefer other check_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Grade a URL's HTTP security headers (CSP, HSTS, X-Frame-Options, Referrer-Policy, Permissions-Policy, COOP, COEP) A-F.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full https URL to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so description's contribution is adding the specific headers and grading scheme A-F. No mention of potential timeouts, rate limits, or error behavior. With good annotations, a 3 is appropriate for adding some context beyond structured fields.
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?
Single sentence is extremely concise, lists key information (headers, grading scale) upfront. No wasted words, every part adds value.
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 covers the core functionality and return format (A-F grade). Could explicitly state it makes a live HTTP request, but that is implied by openWorldHint.
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% (one parameter described as 'Full https URL to check'). Description adds no new parameter details but reinforces the purpose. Baseline 3 is correct since schema already fully documents the parameter.
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?
Description uses specific verb 'Grade' and identifies the resource 'URL's HTTP security headers', listing specific headers. Clearly distinguishes from sibling tools which check other aspects like SEO, SSL, email security, etc.
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?
Purpose is clear (check security headers), but no explicit guidance on when to use this tool versus alternatives or when not to use. Sibling names help differentiate, but description doesn't mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
On-page SEO audit of a URL: title, meta description, H1, canonical, indexability, Open Graph, structured data, image alt coverage, sitemap. Returns an A-F grade.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full https URL to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by detailing the scope of the audit (specific on-page elements) and the grade output, which goes beyond the annotations' safety profile.
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 two sentences long, front-loaded with the tool's purpose and a list of checks, then the output format. No wasted words; every sentence contributes meaning.
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 is checked and what is returned (A-F grade). It could elaborate on the return format, but it is sufficient for an AI agent to understand the tool's function.
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% with one parameter ('url') described as 'Full https URL to check'. The description reiterates this without adding new semantic detail, so baseline score 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 identifies the tool as an on-page SEO audit for a URL, listing specific elements checked (title, meta description, H1, etc.) and the return of an A-F grade. This specificity distinguishes it from sibling tools like check_security_headers or check_ssl.
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 implies use for on-page SEO auditing but does not explicitly state when to use or avoid this tool versus siblings. No guidance on alternatives or prerequisites is provided, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Inspect a domain's SSL/TLS certificate: issuer, expiry, protocol, and flags for expiring/self-signed/mismatched certs.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain, e.g. example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint and openWorldHint, so the tool is read-only and interacts externally. The description adds value by detailing what the tool inspects (issuer, expiry, protocol, flags) without contradicting 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 a single, front-loaded sentence that efficiently conveys purpose and output without any redundant information.
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 simple single-parameter tool with good annotations, the description adequately covers what the tool returns. However, it omits error scenarios like unreachable domains, which could be desirable.
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% with a clear parameter description ('Domain, e.g. example.com'). The description does not add significant extra meaning beyond the schema.
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 inspects a domain's SSL/TLS certificate, listing specific details like issuer, expiry, protocol, and flags. It distinctly differentiates from sibling tools focused on other aspects like security headers or email security.
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 implies usage for checking SSL/TLS certificates but does not explicitly state when to use it versus alternatives or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run a free SimplyScan security & speed scan of a deployed web app URL. Returns a 0-100 score and findings (exposed secrets, missing Supabase RLS, frontend leaks, speed issues). Best for apps built with Lovable, Bolt, v0, Cursor, Replit, etc.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full https URL to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds that the scan is free and uses SimplyScan, implying an external service, and describes the output (score and findings). No behavioral traits contradict 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 two sentences long. The first sentence states purpose and output; the second provides a usage hint. No unnecessary words, front-loaded with key information.
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 one required parameter, no output schema, and sibling tools being more specific, the description covers the tool's purpose, output (score and findings), and suggests ideal use cases. It lacks details about prerequisites (e.g., URL must be deployed) but is sufficient for selecting between this and siblings.
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% with one parameter 'url' having format and description 'Full https URL to check'. The description's 'deployed web app URL' adds minimal additional meaning. Baseline score of 3 is appropriate since the schema already documents the parameter well.
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 runs a security and speed scan on a deployed web app URL and returns a score and findings. It distinguishes from siblings by being a broader scan covering multiple aspects like secrets, RLS, frontend leaks, and speed issues, while siblings are specific checks (e.g., check_security_headers, check_ssl).
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 includes a usage hint: 'Best for apps built with Lovable, Bolt, v0, Cursor, Replit, etc.', implying when to use. It does not explicitly state when not to use or provide alternatives, but the sibling tools serve as alternatives for specific checks. The guidance is clear but could be more explicit about exclusions.
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.
check_ai_visibilitycheck_email_securitycheck_exposed_filescheck_security_headerscheck_seocheck_sslscan_websiteClaiming 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.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
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_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
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
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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Zero-config MCP security scanner for AI-generated apps. 25K+ vulnerability patterns.
Compliance & security scan for your app: secrets, exposed files, headers, privacy, AI-disclosure.
Scan a website for vulnerabilities: OWASP Top 10, CVEs, SSL, headers - with plain-English fixes
Scan any public site for AI-agent visibility; get scored findings, a machine-readable fix pack, and
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of website analysis: AI visibility, email security, exposed files, security headers, SEO, SSL, and a general scan. No two tools overlap in purpose, making it easy for an agent to select the right one.
Six of seven tools follow the 'check_<subject>' pattern, which is clear and consistent. The outlier 'scan_website' breaks the pattern but is still understandable. Overall, naming is predictable with a minor deviation.
Seven tools is an appropriate number for a website scanning/analysis server. It covers key areas (security, SEO, AI visibility) without being overwhelming. Each tool earns its place by addressing a specific need.
The tool surface covers major website concerns: security (headers, SSL, exposed files, email), SEO, and AI visibility. The general 'scan_website' tool likely fills gaps like performance and secrets. Missing some niche checks (e.g., accessibility), but the core is well-covered.
