How to Use the Typeform MCP in LlamaIndex

Q: Can I use LlamaIndex to list all Typeform forms?

Yes. Call the listforms tool and pass that output to LlamaIndex. It indexes the form IDs and titles, making them searchable for later queries.

Q: If I want responses from Typeform, does LlamaIndex help?

It does. After you call getformresponses, LlamaIndex takes those submissions and adds them to your index. You can then query insights from that historical data.

Q: How do I check Typeform themes with LlamaIndex?

You run listformthemes via the MCP Server, and LlamaIndex ingests this list of available themes. You can then query about them later in your knowledge base.

Build searchable knowledge bases from Typeform data using LlamaIndex.

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Connect Typeform MCP to LlamaIndex

Create your Vinkius account to connect Typeform 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 Typeform with LlamaIndex

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Create a searchable index of your Typeform assets.

Don't just call the tools—make them part of your knowledge base. Use `list_forms` and `list_workspaces` to pull metadata about all forms and workspaces. LlamaIndex then indexes this structure, allowing you to search past configurations semantically. You can query what types of forms exist without needing exact keywords.

Query Typeform form details for context.

Need specifics on a form? Run `get_form_details` and index the resulting metadata. Later, you can ask your agent questions like, 'What are the input types of Form X?' and get an answer grounded in the actual API data. This turns raw tool output into reliable, searchable knowledge.

Search past Typeform submissions with LlamaIndex.

Instead of just getting a list of responses, index them using `get_form_responses`. You can then ask complex questions like, 'What were the common answers regarding pricing in Q3?' and get synthesized answers from the historical data. This is how you build RAG applications around your marketing automation.

Setup guide

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

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Common questions about Typeform MCP in LlamaIndex

LlamaIndex indexes the tool output. This means when you retrieve form details or responses, that data becomes part of a knowledge base. You query it using natural language instead of needing specific code steps.

Yes. Call the `list_forms` tool and pass that output to LlamaIndex. It indexes the form IDs and titles, making them searchable for later queries.

It does. After you call `get_form_responses`, LlamaIndex takes those submissions and adds them to your index. You can then query insights from that historical data.

You run `list_form_themes` via the MCP Server, and LlamaIndex ingests this list of available themes. You can then query about them later in your knowledge base.

Since LlamaIndex indexes the results, you must ensure that user response data is properly filtered or anonymized before it enters the vector store. The raw submission records are the key data type here.

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