How to Use the Google Forms MCP in LlamaIndex

Index your Google Forms responses into a searchable knowledge base using LlamaIndex.

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Connect Google Forms MCP to LlamaIndex

Create your Vinkius account to connect Google Forms 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 Google Forms with LlamaIndex

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Ground your LlamaIndex RAG on form data

The `get_form_responses` tool acts as a live feed for your knowledge base. It pulls the latest entries and makes them available for your indexing pipeline. You stop relying on static files. Your agent now searches through actual, current submission data to answer user questions.

Map form metadata for context

Use `get_form_metadata` to understand the context of the data you are indexing. It provides the field definitions needed to label your vectors accurately. This adds a layer of intelligence to your RAG application. The agent knows exactly what each piece of data represents, which makes the retrieval far more precise.

Unified querying of form datasets

LlamaIndex combines this MCP Server output with your existing document stores. You can query across both your forms and your technical manuals at the same time. It removes the silos between your data sources. Your agent treats every form response as a first-class citizen in your searchable index.

Setup guide

Set up Google Forms 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 Google Forms 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 Google Forms tools.",
)
response = await agent.run("List recent Google Forms 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 Google Forms. 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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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Common questions about Google Forms MCP in LlamaIndex

You use the MCP client to pull the data and feed it into your document loader. LlamaIndex then creates vector embeddings that your agent can query later.

It works with any form you have access to via your API token. You just provide the form ID, and the tools handle the rest.

You can loop through multiple form IDs using the tools. Once the data is indexed, LlamaIndex treats the combined output as one searchable knowledge base.

Your data remains private to your specific agent instance. We provide the connection, but you control the index where the data resides.

You decide the frequency based on your own needs. Most users trigger a refresh whenever the agent needs the latest submission context.

Use it with your favorite AI tools

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OpenAI Agents SDK sdk-python

Google ADK sdk-python