Datamagnet

Get post

get_post

Read-onlyIdempotent

Fetch one LinkedIn post by URL: author, text, media, engagement counts and publish time.

Costs 1 credit. This returns the post itself and its totals. To get the people behind those totals, use get_post_engagement.

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": {
      "url": "<url>"
    },
    "name": "get_post"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover read-only, open-world, and idempotent behavior, so the description adds useful context by disclosing the 1-credit cost and the returned data scope. It does not discuss auth or rate limits, but the added credit and routing information is valuable beyond the 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 core action and scope are front-loaded in the first sentence, followed by cost and the key alternative. There is no wasted language.

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?

With an output schema, annotations, cost disclosure, return-field summary, and a sibling route, the definition is nearly complete for a simple post-by-URL lookup. The only notable omission is URL format guidance.

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 description coverage is 0%, so the description carries the burden. It adds that the input is a LinkedIn post URL rather than an ID, but gives no URL format or example, leaving a clear gap.

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?

States a specific verb and resource: 'Fetch one LinkedIn post by URL,' and enumerates the returned fields. It also distinguishes itself from get_post_engagement by clarifying that this returns totals, not the people behind them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent to get_post_engagement when the goal is the people behind engagement totals. The cost statement and 'one post by URL' scope make the intended use clear without leaving ambiguity.

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

All Datamagnet tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.