How to Use the Gravity Forms MCP in LlamaIndex

Q: How do I index Gravity Forms submissions in LlamaIndex?

You use the listentries tool to retrieve your submissions and load them into a LlamaIndex document index. From there, you can run semantic search queries to find specific customer responses based on their meaning rather than exact keywords.

Q: Can LlamaIndex query draft form structures in Gravity Forms?

Yes, by calling getform through the LlamaIndex tool spec, the agent can parse the structure of any draft or active form. It stores this metadata in your index to help guide automated form submissions later.

Q: How does the agent handle form submission results?

The agent uses getformresults to fetch aggregate statistics and submission counts. It then feeds this data into your query engine to answer high-level questions about form performance.

Index your Gravity Forms entries directly into LlamaIndex vector stores to search, query, and analyze submissions without hallucinations.

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Connect Gravity Forms MCP to LlamaIndex

Create your Vinkius account to connect Gravity 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 Gravity Forms with LlamaIndex

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Index active WordPress forms into vector stores

The `list_forms` tool connects your WordPress site to LlamaIndex via our MCP Server, retrieving configurations so you can index your form structures for semantic search. This lets your agent query your available forms using natural language instead of digging through WordPress admin screens. By feeding the output of `get_form` into your vector index, your RAG pipeline gains a deep understanding of your data fields. Your agent can instantly identify which form to use when a user asks to submit specific information.

Build RAG pipelines on Gravity Forms submissions

The `list_entries` MCP tool pulls your WordPress form submissions directly into your LlamaIndex document store. This allows you to run vector queries over historical user entries, turning raw database records into searchable knowledge. When a user asks a question, your agent retrieves the relevant context from `get_entry` and combines it with your local documents. You can also query `list_entry_notes` to see how support agents handled similar submissions in the past.

Sync form feeds and notes with LlamaIndex MCP Server

The `list_feeds` tool exposes active integrations on your WordPress site, letting your LlamaIndex agent verify where data is sent. The agent can check active feeds and run `create_entry_note` to log automated audit trails directly on the form entry. If database updates are required, the agent calls `update_entry` to modify specific fields based on your query results. This ensures your vector index and your live WordPress database stay synchronized without manual data entry.

Setup guide

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

You use the `list_entries` tool to retrieve your submissions and load them into a LlamaIndex document index. From there, you can run semantic search queries to find specific customer responses based on their meaning rather than exact keywords.

Yes, by calling `get_form` through the LlamaIndex tool spec, the agent can parse the structure of any draft or active form. It stores this metadata in your index to help guide automated form submissions later.

You can configure an agent to run semantic analysis on entries retrieved via `list_entries` and call `delete_entry` on flagged spam using the MCP interface. This lets LlamaIndex automate database cleanup based on custom business logic.

The agent uses `get_form_results` to fetch aggregate statistics and submission counts. It then feeds this data into your query engine to answer high-level questions about form performance.

Your WordPress form structures and entry records remain entirely in your private database and your chosen vector index. This MCP Server establishes a direct, secure connection using an ephemeral token, ensuring no customer submission data is ever cached or stored on our platform.

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