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Instagram Account MCP

Instagram Account MCP

by joinhackyard

Write caption options

generate_caption
Read-only

Drafts Instagram caption options—hook, body, CTA, hashtags, and reel on-screen text—from a brief, transcript, image, or video, then checks format limits; nothing is published.

Instructions

Drafts caption options (hook first line, short body, call to action, hashtags, and on-screen hook text for reels) from a description, a transcript file, or the media file itself (images are looked at; videos are transcribed when a transcription model is connected). Applies the template and checks Instagram's limits. Drafts only: nothing is published. Without an AI model it returns a brief so you write them.

Input Schema

NameRequiredDescriptionDefault
countNo
notesNo
formatNoreel
languageNo
templateNo
file_pathNoThe image or video to be posted.
descriptionNoWhat the post is about, key points, audience.
transcript_pathNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations it discloses the important behaviors: it drafts only and nothing is published, images are actually inspected, videos are transcribed only when a transcription model is connected, and without an AI model it degrades to returning a brief. It also notes that Instagram limits are checked, which explains why the output may be constrained.

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?

The purpose is front-loaded in the first sentence with the output shape in parentheses, followed by constraints and the no-model fallback. Dense but each sentence carries information; the long parenthetical in sentence one is the only slightly awkward element.

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?

With no output schema and no required parameters, the description compensates by describing the caption structure produced and the fallback when no model is configured. Gaps remain around the purpose of notes, allowed language values, and where templates come from (list_templates), but the core call contract is clear.

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 coverage is only 25%, so the description has to carry meaning, and it covers three of the eight inputs well: description, transcript_path, and file_path are all implied by the listed sources. The remaining parameters (count, notes, language, format, template beyond "applies the template") receive no explanation of what values to supply or how they affect output.

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?

"Drafts caption options (hook first line, short body, call to action, hashtags, and on-screen hook text for reels)" is a specific verb plus resource and even enumerates the output components. The input sources (description, transcript file, media file) further pin the scope, making it distinguishable from publish_* (this never publishes) and from caption_check or translate_caption.

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 tells the agent which input sources are acceptable (a description, a transcript file, or the media file itself), which is real when-to-use context. It stops short of naming alternatives or exclusions, e.g. when to prefer caption_check, translate_caption, or generate_hashtags instead of or alongside this tool.

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