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Substack MCP Server

Substack MCP Server

by cotletdev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get post engagement

get_post_engagement
Read-onlyIdempotent

Retrieve who liked and commented on a Substack post plus the free signups, paid subscriptions, and unsubscribes it generated, so you can track engagement and growth per post.

Instructions

Who liked and commented on a post, and the subscribers it won and lost.

Returns the Engagement and Growth parts of a post's stats: like and comment counts with the people behind them (name and handle, never email), and the free signups, paid subscriptions and unsubscribes Substack credits to the post. Counts keep changing for days after a send.

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": {
      "post_id": "<post_id>"
    },
    "name": "get_post_engagement"
  }
}

Input Schema

NameRequiredDescriptionDefault
post_idYesPost ID from list_posts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, and the description still adds real value: it discloses the privacy constraint (name and handle, never email) and the eventual-consistency trait that counts keep changing for days after a send. It does not describe response shape, but no output schema exists to rely on.

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?

Three sentences with the headline summary front-loaded and no filler. The opening fragment is a slightly awkward lead-in, but the body is dense and each sentence carries content.

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 one well-documented parameter and no output schema, the description must convey what comes back, and it does by naming the returned data (counts, people with name/handle, signups, paid subs, unsubscribes) and the timeliness caveat. Only the response structure/format is left unstated.

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?

Single parameter with 100% schema description coverage ('Post ID from list_posts'), so the schema does the work. The description adds no format or source guidance beyond what the schema already states, which is the baseline-3 case.

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?

States a specific resource and enumerates what the tool returns: likers/commenters with name and handle, plus free signups, paid subscriptions and unsubscribes. It carves out 'the Engagement and Growth parts of a post's stats,' which implicitly separates it from get_post_stats and get_post_traffic, but never names those siblings outright.

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?

Usage is only implied: an agent can infer this is the tool for per-post engagement detail versus aggregate stats, but there is no explicit 'use this when / use X instead' routing and no stated prerequisites. Adequate but leaves the choice among get_post, get_post_stats and get_post_traffic to inference.

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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