How to Use the FormKeep MCP in LlamaIndex

Q: How do I load FormKeep data into LlamaIndex?

Install llama-index-tools-mcp and set up a BasicMCPClient. Call await mcptoolspec.totoollistasync() and pass the resulting tools to your FunctionAgent.

Q: Can LlamaIndex query specific FormKeep records?

Your agent uses getsubmission to pull exact records when a user asks a highly specific question. It bypasses the vector store and hits the API directly for real-time accuracy.

Index your form submissions into searchable vector stores using LlamaIndex.

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Connect FormKeep MCP to LlamaIndex

Create your Vinkius account to connect FormKeep 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 FormKeep with LlamaIndex

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Index form data via the MCP Server

The `list_submissions` tool pulls your raw form entries straight into your document ingestion pipeline. Your agent reads the batch data and chunks it into queryable nodes for your vector store. You stop writing custom API wrappers. The `BasicMCPClient` handles the connection, letting you focus on building RAG applications that answer questions based on actual user feedback instead of static documents.

Ground queries in live submissions

When a user asks about recent feature requests, your agent executes `list_forms` followed by `get_submission` to fetch real-time context. The output merges with your existing indexed knowledge base. This guarantees your LlamaIndex application answers with factual, up-to-date information. The agent pulls the specific form schema using `get_form_details` to understand the data structure before answering.

Mutate data during RAG workflows

RAG agents typically only read data, but the `delete_submission` tool gives them write capabilities. If an agent detects a spam entry during an indexing run, it can wipe the record immediately. You control this behavior using the `allowed_tools` filter. Pass only the read-focused tools if you want a strict, immutable indexing process.

Setup guide

Set up FormKeep 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 FormKeep 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 FormKeep tools.",
)
response = await agent.run("List recent FormKeep 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 FormKeep. 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 FormKeep MCP in LlamaIndex

Install `llama-index-tools-mcp` and set up a `BasicMCPClient`. Call `await mcp_tool_spec.to_tool_list_async()` and pass the resulting tools to your `FunctionAgent`.

Your agent uses `get_submission` to pull exact records when a user asks a highly specific question. It bypasses the vector store and hits the API directly for real-time accuracy.

You use the MCP tool spec instead of a traditional data connector. Set `include_resources=True` so your agent can read the raw form outputs natively.

You filter the tool inputs at the framework level. The agent only executes `list_submissions` on the form IDs you explicitly allow in the system prompt.

Raw submission texts and user emails pass through a zero-trust architecture. Vinkius requires a single endpoint token, and the temporary memory dumps the payload the moment your RAG pipeline finishes chunking the text.

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