Skip to main content
Glama
BACH-AI-Tools

LinkedIn Api8 MCP Server

get_article_reactions

Retrieve reactions (likes, comments, etc.) for a LinkedIn article by providing its URL. Supports pagination to fetch all reactions.

Instructions

Get article reactions with url

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesExample value: https://www.linkedin.com/pulse/2024-corporate-climate-pivot-bill-gates-u89mc/?trackingId=V85mkekwT9KruOXln2gzIg%3D%3D
pageNoExample value: 1
Behavior2/5

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

With no annotations, the description must disclose behavior. It only states the action, omitting details like read-only nature, pagination handling (despite a page parameter), or any side effects.

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?

While very short, the description sacrifices necessary detail for brevity. It is under-specified, lacking critical instructions for effective use.

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

Completeness2/5

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

Given no output schema, the description should explain return values and differentiate from similar tools (e.g., get_post_reactions). It fails to do so, leaving significant gaps.

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% with examples. The description adds no meaningful information beyond the schema, only restating 'with url'. Baseline score is appropriate.

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 clearly states the verb (Get) and resource (article reactions) with a key input (url). However, it does not differentiate from sibling tools like get_post_reactions or get_article, which could cause confusion.

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?

No guidance is provided on when to use this tool versus alternatives such as get_post_reactions or get_article. The description lacks context for decision-making.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/bachai-linkedin-api8'

If you have feedback or need assistance with the MCP directory API, please join our Discord server