Instagram MCP Server

instagram_user_stats

Retrieve Instagram user statistics including follower counts, engagement metrics, and profile data to analyze account performance and audience insights.

Instructions

Instagramユーザーの統計情報を取得します。

Args:
    username: Instagramユーザー名（@なし）

Returns:
    統計情報の文字列

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": {
      "username": "<username>"
    },
    "name": "instagram_user_stats"
  }
}

Input Schema

Name	Required	Description	Default
`username`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Feb 8, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states what the tool does ('取得します' - gets/fetches) without disclosing behavioral traits like rate limits, authentication needs, error handling, or whether it's a read-only operation. This is inadequate for a tool with no annotation coverage.

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 appropriately sized with three brief sections (purpose, Args, Returns) and is front-loaded with the main purpose. However, the Japanese text might require translation for some agents, and the structure could be slightly more streamlined, but it's generally efficient.

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?

Given the tool has an output schema (which covers return values), no annotations, and a simple input schema with one parameter, the description is minimally complete. It explains the purpose and parameter but lacks behavioral context and sibling differentiation, making it adequate but with clear gaps.

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 description includes an 'Args' section that documents the single parameter 'username' with a note about format ('@なし' - without @), adding meaning beyond the input schema which has 0% description coverage. However, it doesn't fully compensate by explaining what constitutes a valid username or potential constraints, so it meets the baseline.

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 as 'Instagramユーザーの統計情報を取得します' (get Instagram user statistics), which is a specific verb+resource combination. However, it doesn't differentiate from siblings like 'instagram_user_info' or 'instagram_follower_count' which might provide overlapping or related data, so it doesn't reach the highest score.

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. With siblings like 'instagram_user_info' and 'instagram_follower_count' available, there's no indication of what distinguishes this tool's statistics from those other tools' outputs, leaving the agent without usage context.

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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