How to Use the Basis Technologies MCP in CrewAI
Run specialized CrewAI agent teams via this MCP Server to audit, analyze, and report on your Basis Technologies campaigns.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Basis Technologies MCP to CrewAI
Create your Vinkius account to connect Basis Technologies 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 DSP optimization via MCP Server
This Basis Technologies MCP Server connects your CrewAI teams to tools like `list_campaigns` and `get_campaign_performance`. You can assign a Researcher Agent to pull raw campaign metrics while an Analyst Agent processes the trends. Because CrewAI supports shared memory, the Analyst Agent remembers previous performance drops when reviewing new data. Your crew works together to build deep optimization reports without manual data exports.
Automated tactic and creative audits
The `list_tactics` and `get_tactic_performance` tools allow your agents to dissect individual line items. A specialized Media Buyer Agent can identify high-CPA tactics and hand them off to a Creative Agent. The Creative Agent then uses `list_ads` to inspect the actual creatives running under those tactics. This collaborative loop mimics a real marketing team, running completely on autopilot.
Client and brand portfolio mapping
The `list_clients` and `list_brands` tools give your CrewAI agents full visibility into your advertiser accounts. A dedicated Account Manager Agent can map out client structures and assign specific optimization tasks to worker agents. This structure ensures your agents never mix up campaign data between different advertisers. Each crew member stays focused on the correct brand context during execution.
Set up Basis Technologies 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 Basis Technologies tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Basis Technologies Analyst",
goal="Access and analyze Basis Technologies data via MCP.",
backstory="Expert analyst with direct Basis Technologies access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Basis Technologies 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="Basis Technologies Analyst",
goal="Access and analyze Basis Technologies data via MCP.",
backstory="Expert analyst with direct Basis Technologies access.",
tools=mcp_tools,
)
task = Task(
description="List recent Basis Technologies 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 Basis Technologies. 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.
Why Choose Vinkius
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Real-time monitoring
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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One
place for every integration
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Common questions about Basis Technologies MCP in CrewAI
Use it with your favorite AI tools
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