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LinkedIn MCP

LinkedIn MCP

by rohankumbhar-01
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

linkedin_start_oauth

Generate a LinkedIn OAuth authorization URL to start app authorization. Open the URL and sign in so the LinkedIn MCP server can access authorized workflows.

Instructions

Create a LinkedIn OAuth authorization URL. Open it and sign in to authorize the app.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "linkedin_start_oauth"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the interaction step (open URL, sign in) but not prerequisites such as configured client credentials or redirect URI, nor what happens if the user is already authorized. The tool is simple and non-destructive, which limits the stakes, but the bar is higher without 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?

Two short sentences with zero waste. The purpose is front-loaded and the required user action follows immediately.

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?

An output schema exists, so return values need not be explained, and the tool is parameterless. The description covers the essential step but leaves the handoff to linkedin_exchange_code implicit, which would fully round out the OAuth flow for an agent.

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 takes zero parameters, so there is nothing to disambiguate. Baseline 4 applies; the description needs no parameter detail.

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 states a specific verb and resource: 'Create a LinkedIn OAuth authorization URL.' This is clearly distinguishable from data-reading siblings like linkedin_get_my_profile. However, it doesn't explicitly name the follow-up tool linkedin_exchange_code, so the agent must infer the flow split between siblings.

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?

'Open it and sign in to authorize the app' gives the user-facing action but no guidance on when to use this versus linkedin_connection_status (e.g., check first if already authorized) or when to proceed to linkedin_exchange_code. Usage is implied rather than specified.

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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