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Glama
AndresMinakata

LinkedIn MCP Server

Get Inbox

get_inbox
Read-only

List recent LinkedIn inbox conversations to review message threads and identify follow-ups. Use the limit parameter (1-50) to control how many are returned.

Instructions

List recent conversations from the LinkedIn messaging inbox.

The returned inbox text and result URL come from the ordinary messaging inbox. Click-derived conversation references are collected separately after requesting the compose page, which avoided inbox auto-opening on the measured variant. A row contributes a click-derived reference only after its click is followed by an observed different thread path. The scan stops at its first unverifiable click. section_errors.inbox reports that stop or unavailable scan rows; captured inbox text and independently extracted anchors retain their normal handling. A known thread_id can bypass row attribution when calling get_conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of conversations to load (1-50, default 20)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.26.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description does add behavioral context (scan can stop, section_errors.inbox reports that stop, captured text is retained), but it is buried in scraped-page implementation jargon rather than stated as caller-relevant behavior.

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

Conciseness2/5

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

The first sentence is well front-loaded, but the remaining three-to-four sentences dwell on internal scraping mechanics (compose page, measured variant, click-derived references, scan stopping) that a caller does not need. Significant bloat for a one-parameter read tool.

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

Completeness3/5

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 spelled out, and for a single-parameter read tool the definition is more than long enough. However, it spends its length on implementation detail while omitting the one thing an agent needs: how this tool relates to search_conversations and get_conversation.

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?

Only one parameter (limit) exists and schema coverage is 100%, including range and default, so the schema carries the full burden. The description adds nothing about the limit semantics, matching the baseline for a fully documented schema.

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 opening sentence gives a clear verb+resource ('List recent conversations from the LinkedIn messaging inbox'), so the agent immediately knows what the tool returns. It does not distinguish itself from the siblings search_conversations or get_conversation, which list/fetch similar data, so it stops short of a 5.

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?

There is no statement of when to use this tool versus search_conversations or get_conversation. The only routing hint is an oblique trailing remark that 'a known thread_id can bypass row attribution when calling get_conversation,' which is not framed as guidance a caller can act on.

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