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Instagram MCP

Instagram MCP

by nelsonrogers
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Instagram audience

get_instagram_audience
Read-onlyIdempotent

Retrieve Instagram audience demographics and top cities or countries for followers or engaged accounts to analyze who follows or interacts, with age and gender breakdowns.

Instructions

Who the audience is: age, gender, age × gender, top cities and top countries of the followers, or of the accounts that engaged with the content. Rows have counts and share_pct; age also has app_share_pct (the app's own rule) and gender share_of_known_pct.

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": {
      "breakdown": "<breakdown>"
    },
    "name": "get_instagram_audience"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum rows for city and country.
audienceNo'followers' = who follows the account (a snapshot, like the app's audience view); 'engaged' = accounts that interacted with content during the timeframe.followers
breakdownYesage, gender, age_gender (both together), city or country (top 45).
timeframeNoWindow for the engaged audience (Meta's own: the current week or month).this_month

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare this to be a safe, idempotent, open-world read, so the safety profile is covered. The description adds useful semantic context about the derived fields (app_share_pct follows the app's own rule, share_of_known_pct) and row composition, but since an output schema exists, most of that is redundant with structured data.

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?

A single compact passage that front-loads what the tool returns and then explains row composition. No filler sentences, though the dense run-on style and the '×' notation make it slightly harder to scan than separate lines would.

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?

With four well-documented parameters, an output schema, and rich annotations, the definition covers the mechanics adequately. It is thinner on selection guidance—nothing tells the agent when to prefer this over get_instagram_metrics_over_time or get_instagram_report—which leaves a real gap in a crowded sibling set.

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 100% and all four parameters carry descriptions with enum values, so the schema already carries the parameter burden. The description correctly mirrors the breakdown vocabulary (including 'age × gender' mapping to age_gender) but adds no format or interaction detail beyond it; baseline 3 applies.

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 names the resource (audience demographics) and enumerates the exact breakdowns it returns: age, gender, age × gender, top cities, top countries, plus the followers-vs-engaged distinction. It is clearly a read of audience composition rather than of profile or media, though it never explicitly contrasts itself with siblings like get_instagram_profile.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: an agent can infer this is the tool for demographic breakdowns, and the followers/engaged split is explained. There is no explicit 'use this instead of X' guidance and no stated prerequisites such as account scoping or time window constraints beyond the schema.

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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