Can my agent list all connectors in a specific Fivetran group?

Yes. Use the 'list_connectors' tool. Provide the Group ID, and the agent will return a list of all connectors configured within that destination group, including their unique IDs and statuses.

How do I check the details of a specific data destination via chat?

Use the 'get_destination' tool. Provide the Group ID. Your agent will retrieve configuration details about the database or data warehouse connected to that group, providing clear boundary information natively.

Can I audit users and their roles in my Fivetran workspace through the agent?

Absolutely. Use the 'list_users' tool. The agent retrieves all registered users in your workspace with their assigned roles and current statuses, allowing for organizational administrative auditing natively.

Fivetran MCP Server for LlamaIndex 7 tools — connect in under 2 minutes

Name: Fivetran
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 7 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Fivetran as an MCP tool provider through the 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 Fivetran. "
            "You have 7 tools available."
        ),
    )

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

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Fivetran MCP Server

Connect your Fivetran account to any AI agent and take full control of your automated data movement and ELT pipelines through natural conversation.

LlamaIndex agents combine Fivetran tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through the 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

Connector Orchestration — List all connectors within specific groups and retrieve detailed configuration, synced schema details, and setup states natively
Destination Auditing — Retrieve configuration details for destination databases or data warehouses connected to your groups to verify delivery boundaries
Group Management — List all groups (destinations) created in your Fivetran account and extract identifiers and creation metadata limitlessly
Sync State Monitoring — Identify precise active sync statuses and validate physical data movement progress across your organizational pipelines securely
User & Team Oversight — Enumerate all registered users and RBAC teams in the workspace to monitor access levels and administrative status flawlessy
Pipeline Discovery — Analyze specific localized variables decoding active data routes and extracting hidden structural constraints within your ELT flows
Resource Mapping — Retrieve complex structural arrays defining precisely which sources are mapped to which destinations globally across your account

The Fivetran MCP Server exposes 7 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 Fivetran to LlamaIndex via MCP

Follow these steps to integrate the Fivetran 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 7 tools from Fivetran

Why Use LlamaIndex with the Fivetran MCP Server

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

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

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

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

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

Fivetran + LlamaIndex Use Cases

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

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

Data enrichment: query Fivetran 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 Fivetran for fresh data

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

Fivetran MCP Tools for LlamaIndex (7)

These 7 tools become available when you connect Fivetran to LlamaIndex via MCP:

get_connector

Get connector details

get_destination

Get destination for group

get_group

Get group details

list_connectors

List connectors in group

list_groups

List all groups

list_teams

List all teams

list_users

List all users

Example Prompts for Fivetran in LlamaIndex

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

"List all Fivetran groups in my account"

"What is the status of connector 'conn_abc123'?"

"List all users in the Fivetran workspace"

Troubleshooting Fivetran MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Fivetran + LlamaIndex FAQ

Common questions about integrating Fivetran 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 Fivetran tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.