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nurhikam

ig-extract-mcp

by nurhikam

ig_to_screener

Turn any Instagram post, reel, or carousel URL into structured stock screener filters by extracting captions, OCR text, and metadata for PER, PBV, ROE, RSI, and volume.

Instructions

One-shot workflow: URL IG apapun (post/reel/carousel banyak slide) → auto extract caption + carousel → OCR tiap slide → parse jadi filter screener terstruktur. Paling gampang buat user — cukup kasih link IG.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL IG post/reel/carousel
hintNoHint preset: 'value', 'growth', 'breakout', 'dividen', 'ara'
session_userNoUsername IG untuk login jika private

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full transparency burden. It outlines the main processing steps (extract caption/carousel, OCR slides, parse into screener) but does not mention authentication needs, rate limits, side effects, or failure modes.

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 compact and flows logically via arrows, capturing the full pipeline in one sentence. It is slightly dense but remains easy to scan and understand.

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?

The description explains what the tool does and its output type ('filter screener terstruktur'), but does not specify the exact output format, error behavior, or limitations (e.g., supported Instagram URL variants). Given no output schema, this is a moderate gap.

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?

Schema coverage is 100% and each parameter has a clear, if brief, description. The 'hint' parameter lists allowed presets, and 'session_user' explains its optional login purpose, providing useful context beyond bare names.

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 identifies a one-shot workflow that combines extraction, OCR, and parsing into a structured screener. It implies a more convenient alternative to the sibling tools, though it does not explicitly name them.

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?

The phrase 'Paling gampang buat user — cukup kasih link IG' suggests this is the go-to when a user provides an Instagram URL, but it lacks explicit guidance on when to prefer this over the individual sibling tools or what prerequisites exist.

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