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mfarooqone

postifys-mcp

by mfarooqone

postifys_cq_import_rows

Bulk-import pending rows into a Postifys content queue table using JSON. Enables scheduling without n8n when the content queue and publish entitlement are enabled.

Instructions

Native Postifys Content Queue (scheduler without n8n). Requires CONTENT_QUEUE_ENABLED on the server and publish entitlement. Bulk-import pending rows into a table (JSON rows, not multipart CSV).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
tableIdYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It does disclose server configuration and entitlement prerequisites and clarifies the JSON body format. However, it does not state whether the import overwrites existing rows, whether duplicates are allowed, what response to expect, or how imported row status is determined beyond 'pending'.

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 contain all essential information, with the key operational constraints (native queue, requirements, bulk JSON import) front-loaded. No filler or repetition of the schema.

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?

For a bulk import tool with no output schema or annotations, it covers prerequisites, payload format, and the destination concept. It could be more complete by describing typical success/error outcomes or post-import verification, but the existing description is sufficient for an agent to decide and invoke the tool.

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 0%, so the description must compensate. It explains that rows are supplied as JSON rather than multipart CSV and refers to pending rows, which adds meaning to the rows parameter. It does not explain tableId or the optional fields (status, hashtags, postType, description), leaving much to the schema.

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 names a specific operation — bulk-importing rows into a Postifys Content Queue table — and distinguishes it from alternatives by clarifying it is the native scheduler (not n8n) and expects JSON rather than multipart CSV. This makes the tool's purpose unambiguous even among many sibling cq_* tools.

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 clear context: use when interacting with Postifys' native Content Queue and when importing many rows as JSON. It states requirements (CONTENT_QUEUE_ENABLED and publish entitlement) and excludes CSV input, but it does not explicitly name sibling alternatives such as postifys_cq_add_item for single-row inserts.

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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