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nitishnaidi

LinkedIn MCP

by nitishnaidi

start_linkedin_connection

Initiates LinkedIn OAuth and returns an authorization URL to connect your account.

Instructions

Start LinkedIn OAuth and return the authorization URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral transparency burden. It states the action and return value clearly, but it does not disclose whether invoking this tool creates persistent state, whether the authorization URL expires, or whether user interaction is required to complete the flow.

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?

The description is a single, front-loaded sentence with no filler. It communicates both the action and the expected result efficiently, containing only information needed for the agent.

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

Completeness4/5

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

For a zero-parameter tool with no output schema, the description sufficiently covers what the agent needs to know to invoke it: it initiates OAuth and returns the authorization URL. Minor context about the broader OAuth flow and how this relates to complete_linkedin_connection could add value but is not essential.

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, so the input schema is complete and there is nothing for the description to add. The description correctly focuses on the tool's action and output rather than inventing unnecessary parameter details.

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 uses a specific verb ('Start') with a clear resource ('LinkedIn OAuth') and states the concrete output ('return the authorization URL'). This clearly identifies the tool's role and differentiates it from siblings like complete_linkedin_connection and linkedin_connection_status.

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?

The description implies this is the first step in the LinkedIn OAuth flow, which is useful context alongside the sibling tool complete_linkedin_connection. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites or exclusions.

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