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WordPress: Create custom post

wordpress_create_custom_post

Create a new WordPress custom post type entry with title, content, status, and custom fields. Use it to programmatically publish or draft any custom post type on a specified site.

Instructions

[UNIFIED] Create a new post of a custom post type. Supports custom fields/meta data.

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": {
      "site": "<site>",
      "post_type": "<post_type>",
      "title": "<title>",
      "content": "<content>"
    },
    "name": "wordpress_create_custom_post"
  }
}

Input Schema

NameRequiredDescriptionDefault
metaNo
siteYes
titleYes
statusNodraft
contentYes
post_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.13.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv3.4.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already cover the safety profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false), and the description only adds that meta/custom fields are supported. It does not disclose that status defaults to draft, that meta appears to be string-encoded, whether the response returns the new post ID, or what errors occur for invalid post types. For a mutation tool this leaves meaningful gaps.

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?

Two short sentences with the core action front-loaded; nothing is redundant. The brevity is appropriate in form but borders on under-specification given the parameter gaps.

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

Completeness2/5

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

For a six-parameter mutation tool with zero schema descriptions and no output schema, the description is far too thin. An agent cannot tell how to format meta, what site accepts, or what a successful response yields.

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

Parameters2/5

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

Schema description coverage is 0% for six parameters, so the description carries the full burden. It only gestures at 'meta' without explaining the string format (likely JSON), and says nothing about site, post_type (registered type slug), status (defaults to 'draft' in schema but unmentioned), or content expectations.

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 verb and resource ('Create a new post of a custom post type') and names the differentiating feature (custom fields/meta). It is distinguishable from wordpress_create_post only by inference from the name and the phrase 'custom post type' — the description never explicitly contrasts the two.

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

Usage Guidelines2/5

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

No guidance on when to use this versus wordpress_create_post or wordpress_create_page, and no prerequisites such as needing a registered post type, valid site identifier, or authentication. The agent must infer all routing and 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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