How do I create a Concord API token?

You can create an API key via the Concord UI or by calling the `POST /api/v1/apikey` endpoint with your username and password.

What is an instance ID in Concord?

An instance ID is a unique identifier assigned to a specific execution of a process or flow. You use it to retrieve logs, check status, or terminate the execution.

Can I stop a running process?

Yes. Use the 'terminate_process' tool with the instance ID to stop a running execution at any time.

Concord (Workflow Orchestration) MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Concord (Workflow Orchestration)
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Concord (Workflow Orchestration) Specialist",
    goal="Help users interact with Concord (Workflow Orchestration) effectively",
    backstory=(
        "You are an expert at leveraging Concord (Workflow Orchestration) 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 (Workflow Orchestration) "
        "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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* 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 (Workflow Orchestration) MCP Server

Connect your AI assistant to Concord, the open-source workflow orchestration and CI/CD platform. Your agent can manage organizations, projects, and execution processes programmatically — all triggered from natural language commands.

When paired with CrewAI, Concord (Workflow Orchestration) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Concord (Workflow Orchestration) 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

Process Management — List, inspect, and terminate running workflow executions across your Concord projects.
Log Retrieval — Pull execution logs for any process instance to quickly diagnose failures or audit pipeline runs.
Organization & Project Scoping — Browse all organizations and projects configured in your Concord server.

The Concord (Workflow Orchestration) 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 (Workflow Orchestration) to CrewAI via MCP

Follow these steps to integrate the Concord (Workflow Orchestration) 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 (Workflow Orchestration)

Why Use CrewAI with the Concord (Workflow Orchestration) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Concord (Workflow Orchestration) 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 (Workflow Orchestration) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Concord (Workflow Orchestration) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Concord (Workflow Orchestration) 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 (Workflow Orchestration), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Concord (Workflow Orchestration) 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 (Workflow Orchestration) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Concord (Workflow Orchestration) MCP Tools for CrewAI (10)

These 10 tools become available when you connect Concord (Workflow Orchestration) to CrewAI via MCP:

get_process

Retrieve detailed information about a specific process execution

get_process_log

Retrieve the execution logs for a specific process

get_project_details

Retrieve detailed information about a specific project

list_organizations

Retrieve a list of all organizations in Concord

list_processes

Retrieve a list of process executions in Concord

list_projects

Retrieve a list of projects within an organization

list_repositories

Retrieve a list of repositories configured for a project

list_running_processes

Quickly list all currently running processes

start_process

Trigger a new process execution in Concord

terminate_process

Stop a running process execution

Example Prompts for Concord (Workflow Orchestration) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Concord (Workflow Orchestration) immediately.

"Show me the last 10 finished processes in Concord."

"List all organizations available in my Concord instance."

"Pull the logs for execution instance 'inst-58291'."

Troubleshooting Concord (Workflow Orchestration) MCP Server with CrewAI

Common issues when connecting Concord (Workflow Orchestration) 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 (Workflow Orchestration) + CrewAI FAQ

Common questions about integrating Concord (Workflow Orchestration) 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.