How to Use the Openli MCP in CrewAI

Q: Can I restrict which Openli tools a CrewAI agent accesses?

Yes. Import MCPServerHTTP from crewai.mcp and use the toolfilter parameter. This lets you give one agent listconsents while restricting createagreement to another.

Q: What happens if Openli goes down during a CrewAI task?

Your monitor agent should periodically run checkopenlistatus. If the service is unreachable, the agent can pause the crew's execution until connectivity returns.

Deploy a crew of autonomous legal agents in CrewAI to audit vendors, draft agreements, and process DSARs.

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Connect Openli MCP to CrewAI

Create your Vinkius account to connect Openli to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Openli with CrewAI

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Audit compliance across systems

The `list_audit_logs` tool gives your auditor agent full visibility into who changed what inside your privacy settings. A dedicated monitoring agent can scan these logs sequentially to spot anomalies. If the auditor finds a discrepancy, it can pass the context to a reporting agent. This multi-agent setup creates a continuous, automated compliance review without pulling in your actual legal team.

Process privacy requests autonomously

Assign a specialized agent to monitor incoming requests using `list_dsars` and `get_dsar`. When a new request hits the queue, the agent automatically categorizes it by jurisdiction. A secondary fulfillment agent then takes over. It compiles the necessary user data and updates the status, completing the entire Data Subject Access Request lifecycle hierarchically.

Draft policies with the Openli MCP Server

Your researcher agent can pull current vendor details using `list_vendors` and `get_vendor`. It hands that context to a drafting agent equipped with the `create_agreement` tool. The drafter generates a highly specific privacy policy that accurately reflects your actual data processors. You get living compliance documents that update themselves as your vendor stack changes.

Setup guide

Set up Openli MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. 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 Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Openli tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Openli Analyst",
    goal="Access and analyze Openli data via MCP.",
    backstory="Expert analyst with direct Openli access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Openli transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

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="Openli Analyst",
        goal="Access and analyze Openli data via MCP.",
        backstory="Expert analyst with direct Openli access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Openli transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Openli. 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 Openli MCP in CrewAI

Pass the server URL directly into your agent's configuration using `mcps=["https://..."]`. The agent will automatically discover and load the available tools.

Yes. Import `MCPServerHTTP` from `crewai.mcp` and use the `tool_filter` parameter. This lets you give one agent `list_consents` while restricting `create_agreement` to another.

You define a sequential process. Agent A fetches the request via `get_dsar`, Agent B searches your internal databases, and Agent C drafts the final response email.

Your monitor agent should periodically run `check_openli_status`. If the service is unreachable, the agent can pause the crew's execution until connectivity returns.

Vendor processing agreements contain sensitive legal terms and contact details. We wrap the MCP connection in an isolated sandbox that spins down immediately after your agent finishes reading the record.

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