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Instagram Control MCP Server

Instagram Control MCP Server

by official-Arvind
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

instagram_like_post

Like an Instagram post by providing its media ID or URL.

Instructions

Like a post by media ID or URL.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "media_id_or_url": "<media_id_or_url>"
    },
    "name": "instagram_like_post"
  }
}

Input Schema

NameRequiredDescriptionDefault
media_id_or_urlYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description carries full burden but fails to disclose behavioral traits like authentication needs, rate limits, idempotency, or consequences of liking a post.

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?

Extremely concise (one sentence) and front-loaded. However, it may be too brief, lacking detail that could be included without much length.

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 simple mutation tool with an output schema, the basic purpose is clear. However, missing usage guidelines and behavioral context make it less complete than it could be.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning to the parameter by clarifying it accepts either a media ID or a URL, which supplements the schema's bare 'string' type. Schema coverage is 0%, so this value is significant.

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 the action ('Like a post') and the input method ('by media ID or URL'). It distinguishes from sibling tools like 'instagram_unlike_post' and others.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., unlike, comment, save). The description lacks context on prerequisites or scenarios.

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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