Orkes Conductor MCP Server
Orchestrate microservice workflows via Orkes Conductor — list definitions, track running executions, search workflow history, and inspect task states from any AI agent.
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What is the Orkes Conductor MCP Server?
The Orkes Conductor MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Orkes Conductor via 6 tools. Orchestrate microservice workflows via Orkes Conductor — list definitions, track running executions, search workflow history, and inspect task states from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (6)
Tools for your AI Agents to operate Orkes Conductor
Ask your AI agent "Show me all registered workflow definitions." and get the answer without opening a single dashboard. With 6 tools connected to real Orkes Conductor data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Orkes Conductor MCP Server capabilities
6 toolsGet deep state details of a specific Workflow Execution
Get a specific Workflow Definition explicitly by name
List active, running workflow instances by explicit workflow name
List all explicitly registered Task Definitions via Conductor API
List all registered overarching Workflow Definitions via Orkes API
Perform an elastic Search across all Workflow executions
What the Orkes Conductor MCP Server unlocks
Connect your Orkes Conductor cluster to any AI agent and get full visibility into your workflow orchestration layer — definitions, running instances, task states, and execution history.
What you can do
- Workflow Definitions — List all registered workflow definitions with versions and descriptions, or inspect a specific workflow's graph schema with tasks, operators, and branching logic
- Task Definitions — List all registered task definitions available for orchestration within your workflows
- Running Instances — List actively running workflow instances filtered by workflow name to monitor what's currently executing
- Execution Details — Get deep state details for any workflow execution including input/output mappings, task-by-task trace histories, and exceptions
- Workflow Search — Search across all workflow executions using Elasticsearch queries, filtering by status, correlation ID, or workflow type
How it works
1. Subscribe to this server
2. Enter your Orkes Access Key ID, Access Key Secret, and Base URL
3. Start monitoring your orchestrations from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Platform engineers — monitor running workflows and quickly identify stuck or failed executions without opening the Conductor UI
- DevOps teams — search execution history for failure patterns and audit workflow definitions during incident response
- Architects — inspect workflow graphs and task definitions to understand orchestration dependencies
Frequently asked questions about the Orkes Conductor MCP Server
Can I search for failed workflows across my entire history?
Yes. The search tool supports Elasticsearch query syntax — search by status (FAILED, TIMED_OUT), workflow type, date ranges, or correlation IDs. Ask your agent 'show me all failed workflows from the last 24 hours' and it returns matching executions with their IDs, failure reasons, and timestamps.
What's the difference between workflow definitions and running instances?
Definitions are the blueprints — the graph schema with tasks, operators, and branching logic. Running instances are actual executions of those definitions, each with their own input data, current state, and task-by-task progress. Think of definitions as classes and instances as objects.
Does this integration support triggering new workflow executions?
Currently, this integration focuses on observability — listing definitions, monitoring running instances, and searching execution history. It does not trigger new workflow executions. For launching workflows, use the Orkes Conductor UI or direct API calls.
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Connect Orkes Conductor with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Give your AI agents the power of Orkes Conductor MCP Server
Production-grade Orkes Conductor MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.