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 Pydantic AI 10 tools — connect in under 2 minutes

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

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Concord (Workflow Orchestration) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Concord (Workflow Orchestration) "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Concord (Workflow Orchestration)?"
    )
    print(result.data)

asyncio.run(main())

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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 (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.

Pydantic AI validates every Concord (Workflow Orchestration) tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

Follow these steps to integrate the Concord (Workflow Orchestration) MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Concord (Workflow Orchestration) with type-safe schemas

Why Use Pydantic AI with the Concord (Workflow Orchestration) MCP Server

Pydantic AI provides unique advantages when paired with Concord (Workflow Orchestration) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Concord (Workflow Orchestration) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Concord (Workflow Orchestration) connection logic from agent behavior for testable, maintainable code

Concord (Workflow Orchestration) + Pydantic AI Use Cases

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

Type-safe data pipelines: query Concord (Workflow Orchestration) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Concord (Workflow Orchestration) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Concord (Workflow Orchestration) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Concord (Workflow Orchestration) responses and write comprehensive agent tests

Concord (Workflow Orchestration) MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Concord (Workflow Orchestration) to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

Common issues when connecting Concord (Workflow Orchestration) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Concord (Workflow Orchestration) + Pydantic AI FAQ

Common questions about integrating Concord (Workflow Orchestration) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Concord (Workflow Orchestration) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.