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wp_list_pages

Read-only

List pages, posts, or Elementor templates on a connected WordPress site. Returns id, title, slug, type, status, modified for each. When you already know which page you want — and you usually do, because the user gave you its URL — pass search instead of listing everything and scanning: it accepts a full URL, a slug or part of a title, and returns only matches. Listing a 150-page site to find one post_id is several very large responses to learn one integer.

Input Schema

NameRequiredDescriptionDefault
limitNoMax results (1-500, default 100)
detailNoOutput verbosity: "concise" (default) trims long lists to top-25 and caps size; "detailed" returns the full result.
searchNoOnly pages whose URL, slug or title contains this. Paste the page URL directly — it is reduced to its slug. Response reports total_before_filter so an empty result is distinguishable from an ignored filter.
site_idYesThe WordPress site ID
post_typeNopage | post | elementor_library | elementor_component (Editor V4 Components — the documents e-component widgets point at; connector ≥ 0.9.18) (default: page)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

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, non-destructive, and open-world behavior, so the bar is lower. The description still adds useful operational context: `search` accepts a full URL/slug/partial title, and the `detail` verbosity affects response size, which explains the payload-volume risk of unfiltered listing.

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?

Front-loaded with purpose, then the routing heuristic, then the rationale. The final sentence ('several very large responses to learn one integer') is persuasive rather than strictly informational, but it is short and reinforces the guidance, so it mostly earns its place.

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?

With no output schema, the description supplies the returned fields (id, title, slug, type, status, modified), covers the search/verbosity parameters, and gives selection guidance. Nothing an agent needs to invoke it correctly 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?

Schema description coverage is 100%, so all five parameters are already documented, including `search`'s URL-to-slug reduction. The description reinforces the `search` semantics but adds no format or syntax detail beyond the schema, so the baseline 3 for high coverage applies.

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 (List) and the exact resources (pages, posts, Elementor templates) on a connected WordPress site, and names the return fields. It also distinguishes itself from the get-by-id path by steering agents to `search` when the target is known, so an agent can tell it apart from wp_get_page without opening either schema.

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?

Explicit routing guidance: use `search` when the target page is already known (typical, since the user supplied a URL), and use the full listing only otherwise. It even names the alternative cost model ('several very large responses to learn one integer'), leaving nothing 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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