How to Use the Concord CLM MCP in CrewAI

Q: Can my CrewAI agents draft docs via Concord CLM?

They can call createagreement to initiate the process. You can define a persona that creates these documents based on your specific legal requirements.

Q: Does CrewAI support searching Concord CLM records?

Your crew can use searchagreementsbyname to locate specific files. This works even when the agent is part of a larger, multi-agent sequence.

Deploy specialized agents in CrewAI to manage your Concord CLM lifecycle.

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Connect Concord CLM MCP to CrewAI

Create your Vinkius account to connect Concord CLM 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.

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Setup Concord CLM with CrewAI

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Specialized Concord CLM agents for CrewAI

Assign a dedicated 'Legal Assistant' agent in your crew to use `list_agreements`. It keeps your team updated on pending tasks without human intervention. Another agent can take the output from `list_signed_agreements` and archive the files. This hierarchical setup keeps your operations running 24/7.

Collaborative contract handling in CrewAI

Your agents share memory to avoid re-fetching data via `get_agreement`. One agent finds the doc, and the next agent processes the terms. This keeps your CrewAI agents efficient. They don't waste time querying the same endpoint twice when one agent already has the required details.

Secure MCP Server access for CrewAI

Filter the tools your crew can see by using the tool_filter. Only give your 'Signing Agent' access to `send_for_signature` while restricting others. This creates a safer environment for your autonomous operations. You control the blast radius of every agent in the crew.

Setup guide

Set up Concord CLM 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 Concord CLM tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Concord CLM 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="Concord CLM Analyst",
        goal="Access and analyze Concord CLM data via MCP.",
        backstory="Expert analyst with direct Concord CLM access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Concord CLM 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 Concord. 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 Concord CLM MCP in CrewAI

Pass the server URL into your Agent configuration using the mcps parameter. This gives your CrewAI agent access to all 10 available tools.

They can call `create_agreement` to initiate the process. You can define a persona that creates these documents based on your specific legal requirements.

Your crew can use `search_agreements_by_name` to locate specific files. This works even when the agent is part of a larger, multi-agent sequence.

We enforce strict zero-trust boundaries between your agents. Document data is never persisted on our infrastructure, ensuring your legal files stay private.

We use ephemeral transport channels for all communication. Your sensitive contract metadata is deleted as soon as the agent task finishes.

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