How to Use the Widen (Acquia DAM) MCP in LlamaIndex

Q: How does LlamaIndex improve search when querying Widen (Acquia DAM) assets?

LlamaIndex indexes the raw output of tools like getassetdetails. This means you can ask natural language questions—'What are the dimensions of the main logo?'—and get a precise answer grounded in the asset's metadata, which is far better than simple keyword searching.

Q: Can I use LlamaIndex to audit user lists from Widen (Acquia DAM)?

Yes. After calling listaccountusers, you can index that list of users and their roles. Then, your RAG application lets you ask complex questions like: 'Which administrators lack access to the video assets?'

Q: What if I need historical data on asset changes with Widen (Acquia DAM) using LlamaIndex?

You can combine listcollectionassets outputs from different dates and feed them into your index. This allows you to query the evolution of a collection's contents over time, keeping track of added or removed assets.

Q: How does LlamaIndex handle metadata updates for Widen (Acquia DAM)?

If updateassetmetadata changes a field, you simply run that tool and then re-index the resulting data. The updated information immediately becomes part of your searchable knowledge base.

Q: What kind of sensitive data does Widen (Acquia DAM) touch when using LlamaIndex?

This server touches asset metadata, user account details (listaccountusers), and the structural information of collections. Always ensure your knowledge index is secured.

Turn Widen (Acquia DAM) asset metadata into a searchable knowledge base using LlamaIndex.

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Connect Widen (Acquia DAM) MCP to LlamaIndex

Create your Vinkius account to connect Widen (Acquia DAM) to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Widen (Acquia DAM) with LlamaIndex

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Indexing Asset Metadata with LlamaIndex

Don't just read metadata; index it. Use `get_asset_details` to pull comprehensive properties for any asset ID. LlamaIndex takes this structured output and turns it into a vector store entry, making it semantically searchable against your other documents. You can then query past sessions or configurations—like checking all assets in a specific category using `get_category_contents`—and get answers grounded in actual DAM data, not guesses.

Building Knowledge Bases from Collections with LlamaIndex

Need to know what's inside a user-defined grouping? Call `list_saved_collections` to retrieve all collection names. The resulting list of collections can then be indexed, allowing you to ask questions like: 'Which assets are in the 'Q3 Marketing Assets' collection?' This process turns static lists into dynamic knowledge points for your RAG application.

Tracking DAM References with LlamaIndex MCP Server

To track how an asset is being used, query the active references. The `list_cdn_embed_links` tool pulls all HTML snippets and embed links for a given asset ID. This output becomes part of your knowledge index. Later, you can query that index to find out where the asset was displayed without needing to re-run the API call.

Setup guide

Set up Widen (Acquia DAM) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Widen (Acquia DAM) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Widen (Acquia DAM) tools.",
)
response = await agent.run("List recent Widen (Acquia DAM) data")

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Common questions about Widen (Acquia DAM) MCP in LlamaIndex

LlamaIndex indexes the raw output of tools like `get_asset_details`. This means you can ask natural language questions—'What are the dimensions of the main logo?'—and get a precise answer grounded in the asset's metadata, which is far better than simple keyword searching.

Yes. After calling `list_account_users`, you can index that list of users and their roles. Then, your RAG application lets you ask complex questions like: 'Which administrators lack access to the video assets?'

You can combine `list_collection_assets` outputs from different dates and feed them into your index. This allows you to query the evolution of a collection's contents over time, keeping track of added or removed assets.

If `update_asset_metadata` changes a field, you simply run that tool and then re-index the resulting data. The updated information immediately becomes part of your searchable knowledge base.

This server touches asset metadata, user account details (`list_account_users`), and the structural information of collections. Always ensure your knowledge index is secured.

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