How to Use the Hightouch (Reverse ETL) MCP in LlamaIndex

Q: Can LlamaIndex use Hightouch (Reverse ETL) to ground its answers?

Absolutely. By indexing the output of getsync, your agent grounds its responses in live pipeline state. It stops guessing and starts reporting on actual sync configurations.

Index your pipeline metadata into LlamaIndex using the Hightouch (Reverse ETL) MCP server.

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Connect Hightouch (Reverse ETL) MCP to LlamaIndex

Create your Vinkius account to connect Hightouch (Reverse ETL) 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 Hightouch (Reverse ETL) with LlamaIndex

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Index sync history for LlamaIndex

Turn your sync logs into a searchable knowledge base. By running `list_sync_runs`, you can push historical execution data into a vector store for semantic analysis. This lets you ask questions like 'when was the last time the sales sync failed?' and get an answer grounded in the actual run data.

Map sources with LlamaIndex

Your agent uses `list_sources` to build a semantic map of your data origin points. It indexes these sources so your RAG pipeline understands the context of every sync. This makes it easy to find which source feeds a specific model. Your knowledge base becomes a live reflection of your actual infrastructure.

Query Hightouch (Reverse ETL) models in LlamaIndex

Use `list_models` to pull your data models into your LlamaIndex index. Your agent can then reason about your data structure without needing a manual refresh. It treats your model definitions as documents. You get real-time answers about your data mapping directly from your chat interface.

Setup guide

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

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Common questions about Hightouch (Reverse ETL) MCP in LlamaIndex

Install the MCP client and pass the tools to your agent. Once connected, your agent can call `list_syncs` to populate your index with current sync metadata.

Absolutely. By indexing the output of `get_sync`, your agent grounds its responses in live pipeline state. It stops guessing and starts reporting on actual sync configurations.

Since it's an MCP connection, your agent fetches the latest state every time it calls a tool. You get fresh data from `list_sync_runs` whenever you trigger a query.

The server connects via the Vinkius gateway. You provide one endpoint token, and the server handles the session management for your LlamaIndex agent.

Your pipeline metadata is treated as sensitive configuration. The server only reads sync, model, and source definitions and never touches the raw customer records moving through your pipes.

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