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Sabari2005

LinkedIn MCP Server

by Sabari2005

linkedin_send_connection_request

Send a LinkedIn connection request with a personalized note to boost acceptance, while automatically respecting daily and weekly invitation limits to keep your account safe.

Instructions

Send a connection request, optionally with a personalised note (max 300 characters). Notes dramatically improve acceptance rates but free accounts are limited to about 5 per month. LinkedIn also caps invitations at roughly 100/week — this server enforces a conservative daily limit to keep the account safe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoPersonalised message, max 300 characters. Reference something specific and real.
identifierYesA public identifier ("jane-doe-123"), a full profile URL, or "me" for the signed-in user.
Behavior4/5

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

Annotations already indicate non-read-only behavior. The description adds valuable behavior not in annotations: notes improve acceptance, free accounts limited to ~5 notes/month, LinkedIn caps invitations at ~100/week, and the server enforces a daily limit for safety. This is practical behavioral disclosure beyond the structured 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 sentences, front-loaded with the primary action, no filler. Every sentence adds value: the first defines the tool, the second provides essential usage and rate-limit context.

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 simple two-parameter tool, the description fully covers the action, optional parameters, and critical rate limits. Schema covers parameter semantics, no output schema is needed, and no extra return-value explanation is necessary.

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

Parameters3/5

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

Schema coverage is 100%: both 'identifier' and 'note' have descriptive schema text. The description only restates the max 300 characters for note and adds motivational context (acceptance rates), but it does not add new meaning beyond the schema. Baseline 3 is appropriate for high schema coverage.

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 starts with a specific verb and resource: 'Send a connection request' and clarifies the optional personalized note. It clearly distinguishes this tool from siblings like send_message or respond_to_invitation by naming the exact action.

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?

Provides clear context about when to use the tool (for sending connection requests) and important limitations (note limit, weekly cap, daily limit). It does not explicitly state when not to use it or name alternatives, but the context is sufficient for an agent to choose this tool.

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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