instagram-mcp

reply_comment

Reply to any Instagram comment by providing the comment ID and your message, allowing direct engagement with your audience.

Instructions

Tra loi mot binh luan tren Instagram.

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": {
      "comment_id": "<comment_id>",
      "message": "<message>"
    },
    "name": "reply_comment"
  }
}

Input Schema

Name	Required	Description	Default
`message`	Yes
`comment_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 4, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states the action (reply to a comment) without mentioning side effects, authentication requirements, rate limits, or error handling. This is minimal and does not help the agent understand the tool's operational behavior.

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 description is a single concise sentence, which is appropriately sized for a simple tool. It front-loads the core purpose without unnecessary words. However, it sacrifices crucial detail, though that is more a completeness issue than a conciseness one.

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

Completeness2/5

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

Given the tool's simplicity and lack of annotations or output schema, the description is insufficient for correct invocation. It does not clarify how to provide the comment ID or message, nor what response to expect. More detail is needed to enable reliable use, especially for an AI agent.

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

Parameters1/5

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

The input schema has two parameters (comment_id and message) with zero description coverage. The tool description does not explain the meaning or format of these parameters, so the agent has no additional insight beyond their names. This is a significant gap that the description fails to compensate for.

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?

The description clearly states the tool's purpose: replying to a comment on Instagram. It uses a specific verb ('reply') and resource ('comment'), which makes it distinct from sibling tools like get_comments. However, it does not elaborate on any specific behavior or constraints, so it stops short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or related tools such as get_comments or post_photo. The agent is left to infer usage from the tool name and description alone.

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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