Can the AI automatically update a subscriber's custom field values?

Yes! By using the `update_person` tool, your agent can modify any existing custom field values for a specific subscriber identified by their email or ID in seconds.

How do I trigger an automation sequence for a new user?

Simply ask the agent to run the `trigger_automation` action. You'll need to provide the slug of the automation and the target person's email address.

Does this integration allow for bulk deletion of my entire audience?

No. The current toolset focuses strictly on managing individual subscriber records and queries. Destructive actions on the entire audience structure are not exposed to ensure your data remains secure.

Audienceful MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Audienceful
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Audienceful as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Audienceful. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Audienceful?"
    )
    print(response)

asyncio.run(main())

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About Audienceful MCP Server

Connect your Audienceful account to any AI agent and transform how you manage your email marketing and audience data through natural conversation.

LlamaIndex agents combine Audienceful tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

People Management — Create, search, and update subscriber profiles and manage their subscription status across your workspace
Custom Data Fields — Define and manage custom data points to segment your audience with surgical precision
Automation Triggers — Programmatically trigger email sequences and marketing automations for specific users or events
Performance Auditing — Query and analyze campaign performance and audience growth metrics without manual exports

The Audienceful MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Audienceful to LlamaIndex via MCP

Follow these steps to integrate the Audienceful MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Audienceful

Why Use LlamaIndex with the Audienceful MCP Server

LlamaIndex provides unique advantages when paired with Audienceful through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Audienceful tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Audienceful tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Audienceful, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Audienceful tools were called, what data was returned, and how it influenced the final answer

Audienceful + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Audienceful MCP Server delivers measurable value.

Hybrid search: combine Audienceful real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Audienceful to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Audienceful for fresh data

Analytical workflows: chain Audienceful queries with LlamaIndex's data connectors to build multi-source analytical reports

Audienceful MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Audienceful to LlamaIndex via MCP:

create_custom_field

Create a new custom field for your audience members

create_person

You must provide at least an email address. Add a new person to your audience

delete_custom_field

Delete a custom field

delete_person

Use with caution. Permanently remove a person from your audience

get_person

Get details for a specific person by their UID

list_custom_fields

List all custom fields defined in your audience

list_people

You can filter by status or search for a specific email address. List all people in your Audienceful audience

list_send_reports

List recent email send reports

trigger_automation

Manually trigger an automation for a person

update_person

Update an existing person profile

Example Prompts for Audienceful in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Audienceful immediately.

"Search for subscribers who have the 'Company' field set to 'TechCorp'."

"Trigger the 'onboarding-welcome' sequence for [email protected]"

"List all custom fields currently defined in my Audienceful workspace."

Troubleshooting Audienceful MCP Server with LlamaIndex

Common issues when connecting Audienceful to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Audienceful + LlamaIndex FAQ

Common questions about integrating Audienceful MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Audienceful tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.