LinkedIn MCP Server

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list_reactions

Retrieve reactions for a LinkedIn resource by supplying its path and optional query parameters, enabling review of engagement on posts or comments.

Instructions

List reactions for a resource path, e.g. /rest/socialActions/{urn}/reactions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "list_reactions"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes
`query_json`	No		{}

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 5, 2026

TDQS

B3.3/5.0

Behavior2/5

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 only says 'List', implying a read operation, but gives no information about authentication requirements, pagination, response shape, or edge-case behavior. This is minimal disclosure for an operation that likely hits an API endpoint.

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

Conciseness4/5

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

The description is a single focused sentence that front-loads the action and resource, and the example earns its place by clarifying the path format. It is concise without padding, though it could be slightly richer without hurting clarity.

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?

For a simple tool with an output schema and only two parameters, the description is minimally viable: an agent can likely call it correctly using the path example. But the query_json parameter is unexplained, and there is no guidance on when this tool is preferred over related list tools, leaving clear gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the undocumented parameters. It clarifies the 'path' parameter format with an example, but says nothing about 'query_json', leaving a required-by-default parameter underspecified beyond the schema's bare name and default value.

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 names a specific verb ('List') and resource ('reactions for a resource path') and provides a concrete endpoint example. This makes the tool's purpose unambiguous and clearly distinguishes it from sibling tools like list_campaigns.

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?

The description implies it should be used when an agent needs reactions associated with a resource path, and the example reinforces that. However, it provides no explicit when-to-use or when-not-to-use guidance and does not mention alternatives such as list_campaigns.

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