How to Use the Applied Epic MCP in LlamaIndex

Q: Can LlamaIndex filter which Applied Epic tools the agent uses?

Yes. You can pass an allowedtools list to restrict the agent. For example, you might only allow getpolicy and block write access entirely.

Q: How does LlamaIndex handle Applied Epic policy lines?

The framework calls listlines to get the breakdown of coverages like Workers Comp or GL. It then indexes these details so you can run semantic searches across specific liability types.

Q: Will this work with the FunctionAgent in LlamaIndex?

It works perfectly. Call totoollistasync() on your spec and pass the resulting array to your FunctionAgent. The agent will decide when to fetch live client data.

Index your insurance policies and client records directly into LlamaIndex for grounded semantic search.

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Connect Applied Epic MCP to LlamaIndex

Create your Vinkius account to connect Applied Epic 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 Applied Epic with LlamaIndex

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Build an MCP Server RAG pipeline

Stop relying on outdated static exports. This MCP Server lets your LlamaIndex application pull live insurance records by calling `list_policies` and `get_policy` directly from the source. The framework takes those JSON responses and converts them into searchable nodes. When a user asks about upcoming renewals, the query engine searches the vector store and grounds its answer in actual, current policy data.

Index client records and attachments

Your knowledge base needs complete context to be useful. The agent runs `list_clients` to map out your customer base, then calls `get_client` to pull individual details into the index. Insurance workflows rely heavily on documents. By executing `list_attachments`, the system locates files tied to specific accounts so you can ingest those PDFs and forms into your LlamaIndex vector store alongside the structured data.

Query historical activity logs

RAG applications often need to know what happened last week. The tool `list_activities` extracts the task history and communication logs for any given account. If a user asks why a premium went up, the engine can search the indexed activity logs or run `list_lines` to check specific coverage changes. You get answers based on historical API data instead of model hallucinations.

Setup guide

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

Install llama-index-tools-mcp via pip. Set up a BasicMCPClient with your Vinkius URL, then wrap it in McpToolSpec to expose the tools to your query engine.

Yes. You can pass an allowed_tools list to restrict the agent. For example, you might only allow `get_policy` and block write access entirely.

The framework calls `list_lines` to get the breakdown of coverages like Workers Comp or GL. It then indexes these details so you can run semantic searches across specific liability types.

It works perfectly. Call to_tool_list_async() on your spec and pass the resulting array to your FunctionAgent. The agent will decide when to fetch live client data.

We route your queries through a stateless, sandboxed environment. When your indexer fetches client attachments or activity logs, the Vinkius infrastructure processes the transfer ephemerally and destroys the container immediately after.

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