Free public web freshness and response-metadata checks for AI agents.
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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 3.5/5 across 2 of 2 tools scored.
The two tools are clearly distinct: one fetches metadata for a single URL, the other compares metadata for up to five URLs. No overlap or ambiguity.
Both names use the same pattern: 'web_freshness' as base, with 'compare_' prefix for the comparison variant. Consistent verb_noun structure.
With only two tools, the server is minimal but well-scoped for its purpose of checking web freshness. A few more tools (e.g., bulk check) could be justified, but current count is reasonable.
Covers basic single-URL fetch and comparison, but lacks features like custom headers, additional metadata (e.g., content-type), or batch processing beyond five URLs. Some gaps exist.
compare_web_freshnessCompare web freshnessBCompare response metadata for up to five public HTTPS URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, openWorldHint, and destructiveHint which clearly indicate the tool is safe, idempotent, and makes external calls. The description adds only that URLs must be public and HTTPS, which is marginal additional context. No further behavioral traits (e.g., rate limits, timeouts) are disclosed.
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 key information: verb, object, and constraints. No wasteful words or redundant details.
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 complexity of making external HTTP requests (openWorldHint) and the lack of an output schema, the description should provide more context on what 'response metadata' means, error handling for failed URLs, and how results are presented. The sibling tool is mentioned but no guidance on selecting between them is offered, leaving the description incomplete.
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 parameter 'urls' has no schema description (0% coverage) and the tool description does not explain its semantics beyond the general purpose. For a user, it is unclear what format of URIs are accepted or what 'response metadata' specifically includes, so the description fails to compensate for the lack of schema details.
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 verb 'compare', the resource 'response metadata', and the target 'public HTTPS URLs' with a specific limit of up to five. It effectively differentiates from the sibling tool 'web_freshness' which likely handles a single URL.
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 over the sibling 'web_freshness'. The usage context is implied by the tool's name and the sibling list, but no direct guidance on when-not-to-use or alternatives is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web_freshnessCheck web freshnessAFetch public HTTPS response metadata such as status, ETag and Last-Modified without downloading the full page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public HTTPS URL using a DNS hostname. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the tool is safe and non-destructive. The description adds that it only fetches headers, not the full page, which is a useful behavioral constraint but does not detail error handling or response format.
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, clear sentence that front-loads the action and purpose. No redundant words or clauses.
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 tool with one parameter and no output schema, the description provides the key metadata returned (status, ETag, Last-Modified) but lacks details on response structure, error handling, or conditional usage. It is adequate but not fully comprehensive.
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 the parameter 'url' described as 'Public HTTPS URL using a DNS hostname.' The tool description does not add extra meaning beyond the schema, so baseline of 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 fetches public HTTPS response metadata like status, ETag, and Last-Modified without downloading the full page. It distinguishes itself from the sibling tool compare_web_freshness by focusing on a single URL's freshness metadata.
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 when only metadata is needed and not the full page, but it does not explicitly state when to use this tool over compare_web_freshness or provide conditions for non-use. The sibling is named but not contrasted.
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.
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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
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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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