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PlanPost MCP Server
by lukBB

list_posts

Read-onlyIdempotent

Retrieve scheduled and published social media posts, then filter by status, platform, campaign, label, post type, or free text to manage content.

Instructions

List your scheduled and published social media posts. Filter by status, platform, campaign, label, post type, or free text.

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (default: 1)
sortNoSort order: newest (default), oldest, or scheduled (soonest scheduled first)
labelNoFilter by internal label (case-insensitive substring), e.g. 'Garmin CIRQA'
limitNoPosts per page (default: 20, max: 100)
searchNoFree-text search across content, thread segments and label
statusNoFilter by post status ('needs_approval' = waiting on human sign-off; 'partially_published' = some platforms live, at least one failed — see platformResults[].error and .fix)
campaignNoFilter by campaign tag, e.g. 'garmin-cirqa-2026' (matches utm.campaign; slugified automatically)
platformNoFilter by platform (instagram, twitter, linkedin, etc.)
postTypeNoFilter by post type

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds nothing beyond that: no pagination behavior, no mention that results are paged with a default page size, and no hint about what is returned per post. Credit is limited to the filter-scope statement.

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?

Two sentences, front-loaded with the resource and immediately followed by the filter surface. Every clause earns its place with no filler.

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

Completeness3/5

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

For a 9-parameter read tool with no output schema, the definition is adequate on inputs but silent on result shape, pagination defaults and ordering when no sort is given. It is minimum viable rather than complete.

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 the baseline is 3. The description names the same filter axes the schema documents (status, platform, campaign, label, post type, free text) but adds no format, matching semantics or constraints beyond what the schema already provides.

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 ('List ... social media posts') and enumerates the filter dimensions, which cleanly separates it from get_post (single item) and list_pending_approvals. The phrase 'scheduled and published' is slightly narrower than the actual status enum, which also covers draft, failed and cancelled, but the intent is still unmistakable.

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?

The list of filter axes implies when this tool is appropriate, but there is no explicit guidance on when to prefer it over siblings such as list_pending_approvals, get_analytics or list_campaigns, and no exclusions. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.