Skip to main content
Glama
southleft

LinkedIn Intelligence MCP Server

by southleft

get_my_post_analytics

Analyze your LinkedIn post performance to track impressions, engagement metrics, and reach data for data-driven content optimization.

Instructions

Get analytics for your own posts using the Official API.

Uses the r_member_postAnalytics scope (Community Management API) to get accurate impression counts, engagement metrics, and reach data.

Args: post_urns: List of specific post URNs to analyze. If not provided, will fetch your recent posts automatically. limit: If no URNs provided, analyze this many recent posts (default: 10)

Returns analytics including impressions, reactions, comments, shares, and engagement rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_urnsNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the API scope used (r_member_postAnalytics) and mentions that it fetches recent posts automatically if no URNs are provided. However, it doesn't address important behavioral aspects like rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though 'get' implies read-only).

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 well-structured with clear sections: purpose statement, API scope information, parameter explanations, and return value description. It's appropriately sized at 5 sentences, though the API scope detail could be considered slightly technical for some users. Every sentence adds value.

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

Completeness4/5

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

Given the tool has an output schema (so return values don't need explanation in description), 2 parameters with good semantic coverage in the description, and no annotations, the description is reasonably complete. It covers purpose, usage context, parameters, and the type of analytics returned. The main gap is lack of behavioral details like authentication requirements or rate limits.

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

Parameters5/5

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

The description provides excellent parameter semantics beyond the schema. The schema has 0% description coverage, but the description clearly explains both parameters: 'post_urns' as 'List of specific post URNs to analyze' with the behavior when not provided, and 'limit' as 'If no URNs provided, analyze this many recent posts (default: 10)'. This fully compensates for the schema's lack of descriptions.

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 the tool's purpose: 'Get analytics for your own posts' with specific metrics listed (impression counts, engagement metrics, reach data). It distinguishes itself from sibling 'get_post_analytics' by specifying 'your own posts' and mentions the specific API scope used (r_member_postAnalytics).

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 about when to use this tool: for analyzing your own posts with the Official API. It distinguishes from the sibling 'get_post_analytics' by specifying 'your own posts' rather than general post analytics. However, it doesn't explicitly state when NOT to use it or mention all possible alternatives among the many sibling tools.

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/southleft/linkedin-mcp'

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