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softwareone-platform

Adobe VIP Marketplace Docs MCP Server

Get VIPMP code examples

get_vipmp_code_examples
Read-onlyIdempotent

Extract code examples (JSON, curl, bash, python) from a given Adobe VIP Marketplace docs page, with optional language filtering to get the relevant snippets.

Instructions

Extract code examples (JSON / curl / bash / python / etc.) from a specific docs page. Optionally filter by language.

Args: docs_path: Docs path (e.g. "/vipmp/docs/customer-account/create-customer-account"). language: Optional filter — "json", "python", "bash", etc. Matches the language-<x> class on <code> elements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNo
docs_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.17.0
  2. Removedv0.13.1
  3. First observedv0.9.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral detail by explaining that extraction targets `<code>` elements and that language filtering matches the `language-<x>` class.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: a one-sentence overview followed by concise per-argument details. There is no fluff or unnecessary repetition of schema-only information.

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

Completeness5/5

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

With only two parameters, one required, plus annotations and an output schema, the description covers what is needed to invoke the tool correctly: path format, language semantics, and filtering behavior. Nothing essential is missing.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates: docs_path gets a concrete path example, and language gets optionality, allowed value examples, and the underlying matching mechanism. This adds real meaning beyond the bare schema.

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 states a specific verb ('Extract') and resource ('code examples') from a 'specific docs page', making it clear what the tool returns. This resource focus distinguishes it from siblings like get_vipmp_page, list_vipmp_docs, and search_vipmp_docs even without naming them.

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

Usage Guidelines4/5

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

It gives clear usage context: call with a known docs_path to retrieve code examples and optionally narrow by language. It does not explicitly provide exclusions or name alternative tools for full-page retrieval, so it stops short of the top tier.

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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