How to Use the Aimtell MCP in LlamaIndex

Q: Can I index live Aimtell campaign performance in LlamaIndex?

Yes. The agent calls getcampaignperformance to fetch real-time click rates and indexes them directly into your vector store. You can then query performance trends using standard natural language.

Q: How does LlamaIndex use Aimtell subscriber attributes?

Your agent calls getsubscriberdetails to retrieve attributes, then indexes them as metadata. This lets you filter your RAG queries based on specific subscriber characteristics.

Q: How do I retrieve triggered campaigns for indexing?

The agent executes listtriggeredcampaigns to pull automated workflows. It then converts this JSON payload into indexable document nodes for your query engine.

Index active Aimtell campaigns and subscriber segments into your LlamaIndex vector store for instant RAG queries.

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Connect Aimtell MCP to LlamaIndex

Create your Vinkius account to connect Aimtell 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 Aimtell with LlamaIndex

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Semantic search over Aimtell campaign history

The `list_campaigns` tool retrieves your historical push notifications via this MCP integration and feeds them directly into your LlamaIndex document store. The agent indexes the raw campaign copy, click metrics, and timing data into your vector database. You then run semantic search queries over your past dispatches. Instead of manually digging through logs, you ask your agent which messaging angles drove the most clicks.

Ground LlamaIndex RAG in live subscriber data

This MCP Server exposes `get_subscriber_details` to pull live metadata into your index context. The agent combines this fresh data with static documentation to ground its responses in actual user profiles. This setup prevents hallucinations when drafting custom push notifications. The agent knows exactly what attributes exist because it queries the live API before writing a single word.

Index subscriber segments for targeted queries

The agent calls the MCP Server tool `list_segments` to pull your current audience taxonomies into LlamaIndex. It indexes these segment definitions alongside your product catalog to map the best audience for new items. It then uses `list_subscribers` to verify segment sizes before recommending a push campaign. You get a fully indexed, queryable map of your push audience.

Setup guide

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

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Common questions about Aimtell MCP in LlamaIndex

Yes. The agent calls `get_campaign_performance` to fetch real-time click rates and indexes them directly into your vector store. You can then query performance trends using standard natural language.

Your agent calls `get_subscriber_details` to retrieve attributes, then indexes them as metadata. This lets you filter your RAG queries based on specific subscriber characteristics.

Absolutely. You load the MCP Server using the LlamaIndex MCP tool spec, allowing your agent to query subscriber segments and push campaigns dynamically.

The agent executes `list_triggered_campaigns` to pull automated workflows. It then converts this JSON payload into indexable document nodes for your query engine.

Vinkius handles authentication via a single endpoint token and executes all calls in a secure V8 sandbox. Your subscriber metadata and push metrics are processed in memory and never written to persistent Vinkius disks.

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