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Tumblr MCP Server and API by Cotlet

Schedule post in Tumblr

tumblr_schedule_post
Read-onlyIdempotent

Schedule post in the user's own Tumblr account from ChatGPT, Claude or any AI agent. Returns how to do it in Tumblr step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Tumblr Cloud Browser. Tumblr's official API: Tumblr has a full public API v2 with OAuth for posts, queue, drafts, submissions, follows and notes, but no official MCP server (checked 17 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "tumblr_schedule_post"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

With readOnlyHint, idempotentHint and openWorldHint=false already declared, the description's "opens nothing by itself" reinforces the read-only profile and adds the return shape (screens, buttons, fields), which is genuine added context. The closing note about Tumblr's official API v2 and lack of an MCP server is informational but doesn't change how the agent should call the tool, so it doesn't raise the score further.

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

Conciseness3/5

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

The purpose and the return value are front-loaded and clear, but the final sentence about Tumblr's official API, including the parenthetical "checked 17 Oct 2026", is tangential and lengthens the definition without helping an agent invoke the tool.

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?

There is no output schema or input schema, so the description must carry the return semantics, and it does ("returns how to do it in Tumblr step by step (screens, buttons, fields)") plus what the tool does not do. What is missing is any routing guidance against the Tumblr siblings, which keeps it short of complete.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description does not invent or misdescribe any inputs.

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?

The first sentence names the verb and resource ("Schedule post in the user's own Tumblr account") and the second clarifies that the tool returns step-by-step instructions rather than performing the action. This plants it clearly apart from the browser tools, though it does not distinguish it from tumblr_create_post or tumblr_list_queue.

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?

It gives a useful follow-on instruction ("then do it with the cotlet_browser_* tools in the user's Tumblr Cloud Browser"), which tells an agent what to do next. But it never says when to pick this over the sibling tumblr_create_post / tumblr_list_queue, nor any preconditions.

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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