How to Use the Applied Epic MCP in CrewAI
Deploy autonomous agent crews to manage Applied Epic policies and client files.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Applied Epic MCP to CrewAI
Create your Vinkius account to connect Applied Epic to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Multi-agent policy audits in CrewAI
The `list_policies` tool allows your research agent to scan your active book of business for compliance gaps. The agent passes these policy records to an audit agent to flag accounts missing key coverage lines. Your audit agent then calls `list_lines` to verify specific coverages like Workers Comp or GL. This collaborative process runs entirely in the background, presenting your brokers with a clean list of gaps.
Autonomous activity logging via MCP Server
This MCP Server exposes the `create_activity` tool to let your writing agent log client interactions and compliance updates. When a research agent flags a policy issue, the moderator agent instantly writes a task log to the ERP. By integrating `list_activities`, your monitoring agent can track previous logs to avoid creating duplicate tasks. The crew shares this history in its common memory, keeping your ERP records clean and organized.
Automated client and document verification
The `get_client` tool enables your account agent to pull full profile details when a client requests a policy change. The crew coordinates to check if the current contact info matches your database records. Your agent crew then runs `list_attachments` to verify all signed agreements are on file. If any document is missing, the crew flags the account and drafts a request email for the broker to review.
Set up Applied Epic MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Applied Epic tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Applied Epic Analyst",
goal="Access and analyze Applied Epic data via MCP.",
backstory="Expert analyst with direct Applied Epic access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Applied Epic transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="Applied Epic Analyst",
goal="Access and analyze Applied Epic data via MCP.",
backstory="Expert analyst with direct Applied Epic access.",
tools=mcp_tools,
)
task = Task(
description="List recent Applied Epic transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) 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 CrewAI
Use it with your favorite AI tools
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