How to Use the 123FormBuilder MCP in LlamaIndex

Q: What's the setup for using 123FormBuilder with a LlamaIndex agent?

After pip install llama-index-tools-mcp, create a BasicMCPClient with your 123FormBuilder MCP Server endpoint URL. Wrap it in an McpToolSpec and then call totoollistasync() to get the tools for your agent.

Q: How do I get my LlamaIndex agent to read data from a new 123FormBuilder submission?

The agent would use the listformentries tool to check for new submissions. Once it has an entry ID, it passes that to getentrydetails. The data returned by that tool can then be used by the agent or indexed for later retrieval.

Turn your 123FormBuilder account into a queryable knowledge base. LlamaIndex can now ask questions about your forms and submissions.

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Connect 123FormBuilder MCP to LlamaIndex

Create your Vinkius account to connect 123FormBuilder 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 123FormBuilder with LlamaIndex

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Index Your Form Structures

Your agent can call `list_active_forms` and then loop through them, using `list_form_fields` for each one. LlamaIndex ingests this output, creating a vector index of all your form schemas. Now you can ask your agent, "Which forms collect an email address?" and get a real answer. You don't have to manually document your forms anymore. The index becomes your single source of truth. When you need to find a form with a specific field, you query your agent instead of clicking through the 123FormBuilder UI.

Create a Searchable Submission Archive

Point LlamaIndex at your forms. It will use `list_form_entries` and `get_entry_details` to pull all submission data and index it. Your agent can now answer complex questions like, "Summarize feedback from the last 10 survey submissions." This turns your raw submission data into structured, searchable knowledge. Forget exporting CSVs. Your RAG application can now ground its answers in the actual content your users have submitted.

Query Account Configuration with this MCP Server

Let your agent index the output of tools like `list_form_webhooks`. When a developer asks, "Which endpoints are receiving data from the 'New User Signup' form?", the agent can query its knowledge base for the answer. It's configuration as a queryable asset. No more digging through settings pages to find a webhook URL. The agent maintains an up-to-date index of your 123FormBuilder integration points. This is especially useful for onboarding new team members who need to understand the data flow.

Setup guide

Set up 123FormBuilder 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 123FormBuilder 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 123FormBuilder tools.",
)
response = await agent.run("List recent 123FormBuilder 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 123FormBuilder. 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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Common questions about 123FormBuilder MCP in LlamaIndex

After `pip install llama-index-tools-mcp`, create a `BasicMCPClient` with your 123FormBuilder MCP Server endpoint URL. Wrap it in an `McpToolSpec` and then call `to_tool_list_async()` to get the tools for your agent.

LlamaIndex is built for RAG, so its main purpose is to index the output of the tools. When your agent calls `list_active_forms`, LlamaIndex can automatically add the results to a vector store, making your form data queryable.

Yes. You'd build an agent that first indexes all your forms using `list_active_forms` and `get_form_details`. After that, you can ask natural language questions like "find all forms related to customer feedback," and the agent will query its index to answer.

The agent would use the `list_form_entries` tool to check for new submissions. Once it has an entry ID, it passes that to `get_entry_details`. The data returned by that tool can then be used by the agent or indexed for later retrieval.

The MCP Server on Vinkius processes your form data inside a secure, sandboxed V8 Isolate. The server itself doesn't store anything. LlamaIndex will handle the data as you've configured it, but the integration itself is stateless and retains no information after the call completes.

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