How to Use the Dotdigital MCP in LlamaIndex

Q: Can LlamaIndex use Dotdigital tools to find specific contacts?

Absolutely, the agent uses searchmarketingcontacts to find data and then indexes that specific profile. This allows for natural language queries about your contact list.

Index your live Dotdigital marketing data into LlamaIndex for semantic, context-aware retrieval.

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Connect Dotdigital MCP to LlamaIndex

Create your Vinkius account to connect Dotdigital 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 Dotdigital with LlamaIndex

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Build a searchable knowledge base with Dotdigital

The MCP Server allows LlamaIndex to ingest results from `list_email_templates` and other endpoints directly into a vector index. Your agent can then perform semantic searches across your entire marketing library. Stop relying on static documents for your RAG pipeline. This gives your agent a live connection to your actual account assets.

Ground agent responses in real-time marketing data

Use `quick_marketing_health_audit` to feed the agent a summary of current performance metrics. The agent uses this context to ground its reasoning, preventing common hallucinations about campaign status. By indexing these snapshots, you ensure the agent knows exactly what is happening in your account. It's grounded, accurate, and ready for queries.

Query past marketing sessions with LlamaIndex

Store the output of `get_contact_profile` into your index to maintain a historical view of customer interactions. Your agent can compare these profiles against current campaign data to spot trends. This approach turns your API data into a queryable asset. You get answers based on the specific contacts and campaigns you manage every day.

Setup guide

Set up Dotdigital 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 Dotdigital 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 Dotdigital tools.",
)
response = await agent.run("List recent Dotdigital data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dotdigital. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Dotdigital MCP in LlamaIndex

You use the MCP tool spec to fetch data and then pass those results into your LlamaIndex vector store. This creates a persistent, searchable knowledge base of your marketing data.

Absolutely, the agent uses `search_marketing_contacts` to find data and then indexes that specific profile. This allows for natural language queries about your contact list.

Data is fetched only when the agent requests it and is stored locally within your vector index. We use ephemeral, isolated connections for every tool request.

It is built for that purpose. You can mix live API calls with retrieved documents to provide the agent with a complete picture of your marketing strategy.

Yes, the tool spec allows you to define an allow-list. You control exactly which data your LlamaIndex agent can access at any time.

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