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Substack MCP Server

Substack MCP Server

by cotletdev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get post

get_post
Read-onlyIdempotent

Retrieves one Substack post by ID with full Markdown body, title, subtitle, audience, URL, and dates, including paywalled content for draft, scheduled, or published posts.

Instructions

Full post: title, subtitle, body as Markdown, audience, URL and dates.

Returns one post of your publication, draft, scheduled or published, with its full body as Markdown, including the paywalled part. Images come back as URLs. Buttons, embeds and footnotes come back as plain text, so writing the body back with update_draft drops them. A scheduled post also has publish_at.

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"
  }
}

Input Schema

NameRequiredDescriptionDefault
post_idYesPost ID from list_posts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, it discloses important return behavior: the full paywalled body is included, images are URLs, and buttons/embeds/footnotes become plain text. It also notes that scheduled posts include publish_at, which materially helps an agent understand the response.

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 return fields are front-loaded, followed by the full-body/paywall behavior and then the lossy Markdown caveat. The description is compact and every sentence contributes useful information.

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

Completeness5/5

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

There is no output schema, so the description carries the burden of explaining the return shape; it does so well, including field coverage and Markdown limitations. Annotations already cover safety, and no critical invocation detail is missing.

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?

The single post_id parameter is fully documented in the schema as coming from list_posts. The description does not add syntax or alternate lookup behavior beyond what the schema already provides, so the baseline of 3 is appropriate.

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 uses a specific verb and resource: it returns one post with title, subtitle, Markdown body, audience, URL, and dates. It distinguishes this from list-oriented siblings by emphasizing a single post ID and the full body, including the paywalled portion.

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?

It clarifies that the post may be a draft, scheduled, or published, and warns that round-tripping the body through update_draft will lose buttons, embeds, and footnotes. It does not explicitly say when to use this versus list_posts, but the single-post scope is clear.

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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