How to Use the Adversus MCP in CrewAI
Deploy autonomous sales agent teams to manage your dialer campaigns using CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Adversus MCP to CrewAI
Create your Vinkius account to connect Adversus 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.
Coordinate dialer operations with CrewAI agent teams
The `list_active_leads` tool serves as the primary data source for your lead-scouting agent. While that agent filters raw prospects, a separate campaign agent runs `list_campaigns` to find matching outbound targets. This multi-agent setup uses shared memory to coordinate tasks without manual handoffs. They work in sequence to ensure leads are vetted before they touch your active dialing queues.
Automate campaign enrollment using specialized CrewAI roles
The `add_contact_to_campaign` tool enables your operations crew to assign contacts dynamically. This MCP Server allows a moderator agent to trigger the insertion once the research agent confirms the lead's phone number is active. By letting a dedicated agent handle campaign insertions, you eliminate manual data entry. The crew monitors performance metrics and adjusts campaign targets based on real-time dialer feedback.
Run automated pipeline audits across CRM projects
The `list_crm_projects` tool allows an auditor agent to inspect your project structures through our managed MCP Server. It works alongside a lead manager agent running `list_campaign_contacts` to verify that every project has active dialer assignments. If the crew finds a project without assigned contacts, they flag the gap for review. That hands-off auditing process ensures your outbound team always has active lists to call.
Set up Adversus 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 Adversus tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Adversus Analyst",
goal="Access and analyze Adversus data via MCP.",
backstory="Expert analyst with direct Adversus access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Adversus 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="Adversus Analyst",
goal="Access and analyze Adversus data via MCP.",
backstory="Expert analyst with direct Adversus access.",
tools=mcp_tools,
)
task = Task(
description="List recent Adversus 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 Adversus. 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 Adversus MCP in CrewAI
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