Threads MCP

Check the daily publishing quota

get_publishing_limit

Read-onlyIdempotent

Check how much of the 24-hour posting quota remains for a Threads profile before bulk actions, preventing mid-run failures when limits are exhausted.

Instructions

How much of the rolling 24-hour quota this profile has spent. Threads allows 250 posts, 1,000 replies and 100 deletes per 24 hours, and refuses everything once a quota is gone. Check this before a bulk run rather than discovering it halfway through.

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": "get_publishing_limit"
  }
}

Input Schema

Name	Required	Description	Default
`account`	No	Which connected Threads profile to act as, by username (for example 'thenavidm'). Defaults to the first connected profile. Call list_accounts to see them.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond that: the quota is rolling over 24 hours, specific action limits, and that Threads refuses everything once any quota is exhausted. This helps the agent understand why the check matters.

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 description is compact and information-dense. It front-loads the core semantic, then provides the quota limits and the practical operational recommendation, all in three short sentences with no filler or redundancy.

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?

For a simple read-only tool with one optional parameter and no output schema, the description is complete: it explains the quantity being measured, the platform limits, the consequence of exhaustion, and when to invoke the tool. Nothing essential is missing for an agent to select and call it correctly.

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 parameter, account, is already fully documented in the schema with a description, default behavior, an example, and a pointer to list_accounts. Schema coverage is 100%, so the description does not need to add parameter-level detail; it adds no new param semantics, making baseline 3 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 clearly states what the tool does: reports how much of the rolling 24-hour publishing quota has been spent. It gives concrete limits for posts, replies, and deletes, making the resource and semantics immediately identifiable and distinct from sibling tools like create_post or get_posts.

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 provides an explicit usage cue: check before a bulk run rather than discovering the quota is gone halfway through. There is no alternative quota tool among siblings, so the lack of an explicit 'when not to use' is not a significant gap.

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