Orkes Conductor Connector for AI agents.
6 live capabilities
Monitor and debug microservice workflows with real-time execution data.
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Why people use Orkes Conductor
Orkes Conductor for Debugging Microservice Failures
With this Connector, you just ask your agent. It pulls the exact execution state, shows you the input that caused the crash, and points to the specific task that failed. You get the answer in seconds without ever leaving your chat interface.
What Vinkius changes
You get a direct command line for your microservice orchestration layer via your AI agent.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Debugging a failed order
An engineer asks the agent why order #123 failed.
- Real-world use case 02
Checking live sync status
A DevOps lead asks for all active data syncs.
- Real-world use case 03
Auditing production failures
A platform engineer asks to find all failed payments today.
Complete set · 6capabilities
The complete Orkes Conductor capability set.
These are the exact actions your AI can choose when you ask it to work with Orkes Conductor.
01—03
3 capabilities in this set.
Part of 6 available through Orkes Conductor.
- 01 Capability
List running
Filter and see which workflow instances are currently active right now. It's the fastest way to check live status.
- 02 Capability
Get execution
Pull the full input, output, and trace history for a specific execution. This is your primary capability for deep debugging.
- 03 Capability
Search workflows
Query your entire history using filters like correlation ID or status. Use this to find specific needles in the haystack.
04—06
3 capabilities in this set.
Part of 6 available through Orkes Conductor.
- 04 Capability
List workflow defs
Get a full list of all registered workflow definitions in your cluster. This helps you see the scope of your orchestration.
- 05 Capability
Get workflow def
Pull the specific graph schema and task logic for a named workflow. Use this to understand how a process branches.
- 06 Capability
List task defs
See every available task definition registered within your environment. This clarifies what actions your workflows can take.
Set up in minutes
One URL. Then ask Orkes Conductor to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Orkes Conductor from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Orkes Conductor, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Orkes Conductor for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Orkes Conductor URL.
- Step 03
Save and start
Save the connection and enable Orkes Conductor in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"orkes-conductor": {
"url": "https://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Orkes Conductor
Open Agent mode in chat and ask: "Using Orkes Conductor, help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"orkes-conductor": {
"url": "https://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Orkes Conductor
Ask Copilot: "Using Orkes Conductor, help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"orkes-conductor": {
"url": "https://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Orkes Conductor
Open Cascade and ask: "Using Orkes Conductor, help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"orkes-conductor": {
"url": "https://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Orkes Conductor
Ask Cline: "Using Orkes Conductor, help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add orkes-conductor --transport http "https://edge.vinkius.com/vk_preview_RrYCpOWyMYAgc2byLtphBnT5DV3QN0zxvc3KjL5z/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Orkes Conductor
Ask Claude: "Using Orkes Conductor, show me...". 6 tools are ready
Where the request belongs
Work Orkes Conductor can move forward.
This is for the platform engineer who's tired of clicking through dashboards at 2am to find out why a production pipeline stalled, or the DevOps lead who needs to audit workflow logic without hunting for docs.
Platform Engineer
Uses this to monitor live microservice executions and quickly identify where a process is stuck.
DevOps Engineer
Queries execution history to find failure patterns and debug production incidents.
Solutions Architect
Inspects workflow graphs and task definitions to understand system dependencies.
Build the capability set
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Bring your own AI
Change the model, client or framework. Keep Orkes Conductor connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Orkes Conductor.
The practical details behind the request, access and result.
Can Orkes Conductor MCP help me find why a specific order failed?
Yes. You can ask your agent to find a specific order ID or correlation ID, and it will pull the exact execution state, showing you the error message and the specific step where it failed.
How does Orkes Conductor MCP help my DevOps team?
It gives your team a way to monitor live executions and search through historical failures using plain English instead of clicking through multiple dashboard tabs.
Can I see all my active workflows at once?
Absolutely. You can ask your agent to list all running instances, and it will provide a summary of what is currently executing across your cluster.
Does Orkes Conductor MCP support searching for correlation IDs?
Yes, it can search across your entire execution history using filters like correlation IDs, workflow types, or specific statuses.
How do I use Orkes Conductor MCP to check task status?
Once connected, you just ask your agent which tasks are running. It will query the orchestration layer and report back on the current state of those tasks.
Can Orkes Conductor MCP show me the logic of a specific workflow?
Yes. The agent can pull the graph schema for any registered workflow definition, letting you see the branching logic and task sequence in your chat.
Can I search for failed workflows across my entire history?
Yes. The search capability 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.
One connection away
Give your agent a direct line to Orkes Conductor.
Connect Orkes Conductor once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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