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AmmYoo7

linkedin-safe-mcp

by AmmYoo7

login

Start LinkedIn OAuth authentication by returning an authorization URL for the user to open in a browser. After the local callback completes, call auth_status to confirm.

Instructions

Start the LinkedIn OAuth login. Returns an authorization URL — show it to the user and ask them to open it in a browser (it may also open automatically); the local callback completes the flow. Afterwards, call auth_status to confirm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYes
authorization_urlYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it discloses that the browser may open automatically, that the local callback completes the flow, and that login is not confirmed until auth_status is called. It doesn't cover edge cases like URL expiration or failure handling, but covers the essential interactive behavior.

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?

Two tight sentences deliver purpose, required user action, callback behavior, and the follow-up verification step with no filler. The critical instruction to show the URL is front-loaded.

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?

For a zero-parameter interactive OAuth tool, the description provides the full invocation contract: what is returned, what the agent must tell the user, how the flow completes, and how to verify success. The output schema can cover the URL's structured details, so no major context is missing.

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?

The tool has zero parameters and 100% schema coverage, so there is no parameter ambiguity for the description to resolve. The description correctly avoids inventing parameter guidance.

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 states a specific verb and resource ('Start the LinkedIn OAuth login') and clarifies the concrete output ('Returns an authorization URL'). It makes the tool's role distinct from siblings like auth_status and logout without ambiguity.

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

Usage Guidelines4/5

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

It gives clear operational context: show the URL to the user, have them open it, and then call auth_status to confirm. It implies the alternative boundary—this tool starts the flow, while auth_status verifies completion—but does not explicitly say when not to use login.

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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