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Glama

Browser Discover Apis

browser_discover_apis

Discover background API endpoints (fetch/XHR) used by a page, including internal and undocumented APIs, via live observation or captured traffic.

Instructions

Discover background API endpoints (fetch/XHR) used by the page — including internal/undocumented APIs, from capture or live observation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabNo
limitNo
sessionNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the data source (capture or live) but does not state whether the tool is read-only, whether prior network capture is required, what happens if no APIs are found, or if it has any side effects on the page or session. This is a significant gap for a discovery tool that might modify state indirectly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is a single sentence that is direct and front-loaded with the core purpose. There is no filler or redundant wording. It could be slightly more structured with usage notes, but it is appropriately concise for the amount of information it conveys.

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

Completeness2/5

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

The tool has three parameters with no schema descriptions, no annotations, and only a minimal description. Although an output schema exists (which may cover return values), the description omits prerequisites (e.g., whether capture must be active), parameter semantics, and behavioral traits. An agent cannot reliably call this tool correctly without further inference or external documentation.

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

Parameters1/5

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

Schema description coverage is 0% and the description mentions none of the three parameters (tab, limit, session). The description does not explain what 'tab' refers to, how 'limit' constrains results, or how 'session' is used. Since the schema provides no descriptions, the description must compensate, but it offers nothing about parameter semantics.

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

Purpose5/5

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

The description clearly states a specific action (discover), a precise resource (background API endpoints used by the page), and narrows scope to fetch/XHR, including internal/undocumented APIs. This distinguishes it from sibling network tools like browser_network_list, which list observed requests rather than discover endpoints. The phrase 'from capture or live observation' adds context that it works across two modes.

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

Usage Guidelines2/5

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

The description implies usage via 'from capture or live observation' but does not explicitly state when to prefer this tool over siblings like browser_network_capture_start, browser_network_list, or browser_evaluate. It neither names alternatives nor gives conditions for selection, leaving the agent to infer. No explicit 'use this when...' guidance is present.

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