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kaistenberg

MCP Server for LinkedIn

by kaistenberg

Get Feed

get_feed
Read-only

Retrieve posts from your LinkedIn feed using your logged-in browser session. Specify the number of posts to fetch, up to 50.

Instructions

Get posts from the authenticated user's LinkedIn feed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_postsNoNumber of posts to fetch (1-50, default 10). Posts are loaded in batches of ~5 as the page scrolls, so the actual count may slightly exceed the target.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 description doesn't need to repeat safety traits. The description itself adds no behavioral context beyond the purpose; the parameter schema mentions batch loading behavior, but that is not part of the description. Thus, the description provides minimal value beyond 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?

The description is a single, front-loaded sentence that precisely states the tool's function. No unnecessary words or repetition, making it highly concise and effectively structured.

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?

Given the tool's simplicity, existing output schema, and rich annotations, the one-sentence description is sufficient. The read-only annotation covers safety, the schema covers parameters, and the output schema covers return values, so the description fills the remaining purpose gap completely.

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?

The input schema has 100% parameter description coverage, including default, min, max, and batch loading behavior. The tool description adds no extra parameter meaning. With full schema coverage, a baseline of 3 is appropriate.

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 clearly states a specific verb and resource: 'Get posts from the authenticated user's LinkedIn feed.' It distinguishes itself from siblings like get_company_posts (company feed) and search_posts (search), making the tool's purpose explicit.

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?

The description provides clear context: it is for the authenticated user's own LinkedIn feed, not for company posts or search results. While it doesn't explicitly name alternatives or exclusions, the context is unambiguous enough for an agent to decide when to use it.

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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