DAM Butler MCP

An MCP server that gives ChatGPT Enterprise and Claude natural language access to Breville's Vault DAM system.

Transforming how teams find brand assets using natural language and AI

Built as a MVP prototype. Demoed to product leadership September 2025. Architecture adopted and taken to production

by the Breville product engineering team.

▶️ Watch the demo

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The Problem

Breville's Vault DAM held thousands of product images, brand

assets, and marketing materials across global markets.

Finding the right asset required knowing the exact folder

structure, taxonomy, or metadata tags. Non-technical users —

regional brand managers, marketers, content producers — had

to ask someone who knew the system.

That created a repeatable bottleneck. DAM Butler removes it.

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What It Does

Translates natural language into structured DAM API queries.

Ask:

"Find the Barista Express hero shot in white, approved for

EU markets, updated after January 2025"

Get back: the right asset, with metadata, directly in chat.

No taxonomy knowledge required. No folder navigation.

Architecture

flowchart TD
    A(["👤 User Prompt
    ChatGPT Enterprise · Claude Desktop"])

    A --> B

    subgraph MCP ["  🔧  DAM Butler MCP Server  "]
        direction TB
        B["🧠 Intent Parser
        Natural language → structured query"]

        B --> C

        C["🔄 Clarification Loop
        Resolves ambiguous queries before API call"]

        C --> D

        D["🗂️ Metadata Normaliser
        Harmonises field names across global regions"]

        D --> E

        E["🔌 Vault API Connector
        Breville DAM integration"]
    end

    E --> F

    F[("🗄️ Vault DAM · Brandfolder")]

    F --> G

    G(["📦 Asset Results returned to user
    with metadata · preview · download link"])

    style MCP fill:#1a1a2e,stroke:#4a9eff,stroke-width:2px,color:#ffffff
    style A fill:#0f3460,stroke:#4a9eff,stroke-width:2px,color:#ffffff
    style B fill:#1a1a2e,stroke:#e94560,stroke-width:1.5px,color:#ffffff
    style C fill:#1a1a2e,stroke:#e94560,stroke-width:1.5px,color:#ffffff
    style D fill:#1a1a2e,stroke:#e94560,stroke-width:1.5px,color:#ffffff
    style E fill:#1a1a2e,stroke:#e94560,stroke-width:1.5px,color:#ffffff
    style F fill:#16213e,stroke:#4a9eff,stroke-width:2px,color:#ffffff
    style G fill:#0f3460,stroke:#4a9eff,stroke-width:2px,color:#ffffff

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Vault DAM (Brandfolder)

Stack: MCP protocol · Claude API · ChatGPT Enterprise

Custom GPT · Brandfolder/Vault API · Node.js

Development approach: Built using Claude and ChatGPT in

parallel. Used Contextus (beta) to maintain shared context

across model switches — eliminating cold-start repetition

in multi-LLM prototyping workflows.

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Key Engineering Decisions

Clarification before execution

Ambiguous queries returned oversized result sets. Fixed with

a clarification question loop that runs before the API call,

not after. Reduces noise, improves user trust.

Metadata normalisation layer

Asset metadata field names were inconsistent across Breville's

regional markets (US, AU, UK). Added a normalisation step that

harmonises field names before applying filters. Without this,

region-specific queries silently failed.

Why MCP over direct API integration

MCP enforces a strict tool contract between the LLM and the

API. Given Vault's strict schema requirements, MCP prevented

hallucinated field names from reaching the API layer — a

critical reliability improvement over unconstrained function

calling.

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What It Generalises To

Any large structured asset or knowledge repository where

non-technical users need natural language access:

• Legal document and contract management
• Product Information Management (PIM)
• Enterprise content repositories
• Compliance and audit libraries
• Internal knowledge bases

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Outcome

Prototype demoed September 2025. Product team adopted the

architecture and shipped it as an internal tool for Breville's

global brand and content teams.

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Note on Repository

This is a sanitised version of the original prototype.

API credentials and Breville-specific endpoints have been

replaced with environment variable references and mock

connectors for public sharing.