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Glama

1cent Web Intelligence for AI Agents

Url Headers

web.url.headers
Read-onlyIdempotent

Return allowlisted response headers only. Use only for public HTTP(S) resources; it does not execute JavaScript or bypass access controls. Pass url as an absolute public HTTP(S) URL. Keep fresh=false to allow cache reuse; set fresh=true only when a new upstream fetch is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute public HTTP or HTTPS URL to inspect. Private, loopback, link-local, metadata-service and otherwise SSRF-sensitive destinations are rejected.
freshNoSet true only when a new upstream fetch is required; false allows the bounded cached result and is cheaper for the origin.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
toolYes
qualityNo
url_finalYes
checked_atYes
from_cacheYes
request_idYes
content_hashYes
url_requestedYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, non-destructive. Description adds valuable context: it does not execute JavaScript or bypass access controls, and it returns only allowlisted headers, implying some filtering. No contradictions 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences: one for purpose, one for usage constraints, one for fresh parameter. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, output schema existence, and annotation coverage, the description provides all necessary information (purpose, constraints, parameter guidance). No gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers both parameters (100%). Description adds meaningful usage guidance for the 'fresh' parameter, explaining cache reuse and cost implications, which goes beyond the schema's technical description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns allowlisted response headers for public URLs. It distinguishes itself from many sibling url tools by specifying it returns only headers and is limited to public resources, but does not explicitly compare with similar tools like web.url.security_headers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides guidance on using for public HTTP(S) resources only, not executing JS or bypassing access controls. Explains when to set fresh=true versus false. However, it does not explicitly tell when to choose this tool over other url header-related siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlap exists among text extraction tools (url_extract, url_text, url_markdown, url_rag_chunks). Descriptions help differentiate them, so disambiguation is mostly clear.

Naming Consistency5/5

All tools follow a consistent prefix (catalog_, demo_, site_, url_) and use lowercase snake_case with descriptive names. Conventions are uniform throughout.

Tool Count5/5

35 tools cover a comprehensive range of URL and site analysis functions without feeling bloated. Each tool serves a specific purpose, and the count is appropriate for the server's scope.

Completeness5/5

The tool set covers all major aspects of URL analysis: health, content, metadata, change detection, site discovery, and security. No obvious gaps for the stated domain.

Resources