How do I get my Concord API key?

Log in to the Concord web app, go to **Global Settings > API Keys**, and generate a new key. Copy it and paste it into the authentication field below.

Does this work with the Sandbox environment?

Yes. Set 'Use Sandbox?' to true in the credentials configuration to connect to the UAT environment instead of production.

Can I create documents from templates?

Yes. When using the 'create_agreement' tool, you can specify a templateId to generate a document based on a pre-existing template.

Concord CLM MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Concord CLM
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Concord CLM through Vinkius, pass the Edge URL in the `mcps` parameter and every Concord CLM tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Concord CLM Specialist",
    goal="Help users interact with Concord CLM effectively",
    backstory=(
        "You are an expert at leveraging Concord CLM tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Concord CLM "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Concord CLM MCP Server

Connect your AI assistant to Concord, the Contract Lifecycle Management (CLM) platform that centralizes how your team drafts, negotiates, signs, and stores contracts.

When paired with CrewAI, Concord CLM becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Concord CLM tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Agreement Lookup — Search and retrieve any contract by name, ID or status directly through your AI chat.
Signature Workflows — Send agreements out for e-signature to internal or external parties without leaving your conversation.
Template-Based Creation — Create new agreements from pre-approved templates, automatically populating fields and routing them for review.

The Concord CLM MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Concord CLM to CrewAI via MCP

Follow these steps to integrate the Concord CLM MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Concord CLM

Why Use CrewAI with the Concord CLM MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Concord CLM through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Concord CLM + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Concord CLM MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Concord CLM for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Concord CLM, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Concord CLM tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Concord CLM against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Concord CLM MCP Tools for CrewAI (10)

These 10 tools become available when you connect Concord CLM to CrewAI via MCP:

create_agreement

Create a new agreement in Concord

get_agreement

Retrieve detailed information about a specific agreement

get_current_user

Retrieve details of the currently authenticated user

list_agreements

Retrieve a list of agreements from Concord CLM

list_signed_agreements

Quickly list all fully signed agreements

list_templates

Retrieve a list of document templates available in Concord

list_users

Retrieve a list of all users in your Concord organization

list_webhooks

Retrieve a list of configured webhooks

search_agreements_by_name

Find agreements by their name

send_for_signature

Trigger the signature process for a specific agreement

Example Prompts for Concord CLM in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Concord CLM immediately.

"Show me all signed contracts in Concord."

"Send agreement 'agr-4521' for signature."

"Check the status of agreement ID 'agr-8901'."

Troubleshooting Concord CLM MCP Server with CrewAI

Common issues when connecting Concord CLM to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Concord CLM + CrewAI FAQ

Common questions about integrating Concord CLM MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.