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Visual Studio Code supports MCP servers through the GitHub Copilot extension. With the Orq MCP integration, access the Orq.ai workspace directly from Copilot Chat and the editor environment.

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Prerequisites

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Installation

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Add MCP Server

  1. Open the Command Palette with ⌘⇧P (macOS) or Ctrl+Shift+P (Windows/Linux)
  2. Search for and select MCP: Add Server
  3. Select HTTP (HTTP or Server-Sent Events) as the server type
  4. Enter the server URL: https://my.orq.ai/v2/mcp
  5. Name the server orq when prompted
VS Code will create or update a .vscode/mcp.json file in the workspace root. Open it and replace the contents with:
When connecting to the server for the first time, VS Code will prompt for the Orq.ai API key and store it securely in the OS secret store. The key is never written to disk.

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Verification

  1. Open Copilot Chat with ⌃⌘I (macOS) or Ctrl+Alt+I (Windows/Linux)
  2. Ask:
If the integration is working, a list of AI models from the workspace will appear. To check server status at any time, open the Command Palette and run MCP: List Servers.

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Available Commands

Use natural language to ask Copilot to perform these operations:
  • Create an agent with custom instructions and tools
  • Get agent configuration for [agent-key]
  • Update agent [agent-key] with new instructions or model
  • Configure agent with evaluators and guardrails
  • Invoke agent [agent-key] with input [message]
  • Retrieve agent response [response-id]
  • Create a deployment called [deployment-key]
  • Get deployment configuration for [deployment-key]
  • Create a skill called [skill-key]
  • List all skills in my workspace
  • Get skill [skill-key]
  • Update skill [skill-key]
  • Delete skill [skill-key]
  • Get analytics overview for my workspace
  • Show me workspace metrics for the last 7 days
  • Query analytics filtered by deployment ID
  • Create a dataset called "customer-queries"
  • List all datapoints in dataset [dataset-key]
  • Add datapoints to dataset [dataset-key]
  • Update datapoint [datapoint-id]
  • Delete specific datapoints in dataset [dataset-key]
  • Delete dataset [dataset-key]
  • Create an experiment from dataset [dataset-key]
  • List all experiment runs
  • Export experiment run [run-id] as CSV
  • Run experiment and auto-evaluate results
  • Get evaluator configuration for [evaluator-key]
  • Create an LLM-as-a-Judge evaluator for tone
  • Create a Python evaluator to check response length
  • Add evaluator to experiment [experiment-key]
  • Update evaluator [evaluator-key] with a new prompt
  • Update Python evaluator [evaluator-key] with revised code
  • List traces from the last 24 hours
  • Show me traces with errors
  • Get span details for trace [trace-id]
  • Find the slowest traces from today
  • Show all traces for thread [thread-id]
  • List all available chat models
  • List all available embedding models
  • Invoke model [model-id] with prompt [message]
  • Search for datasets named "customer"
  • Find experiments in project [project-id]
  • List directories in project [project-id]
  • Search the Orq.ai docs for [topic]
  • Delete agent [agent-key]
  • Delete experiment [experiment-key]
  • Delete evaluator [evaluator-key]
  • Delete prompt [prompt-key]
  • Delete knowledge base [knowledge-base-key]
Use delete_dataset to delete a dataset along with all its datapoints.
See the MCP Quickstart for the full tool reference and examples.

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Troubleshooting

  1. Open the Command Palette and run MCP: List Servers
  2. Select the orq server and choose Show Output to view logs
  3. Restart VS Code and reconnect. VS Code will prompt for the API key again on first connection
  1. Confirm the API key is valid in Workspace Settings → API Keys
  2. Ensure the API key has the necessary permissions
  3. Try regenerating the API key, then restart VS Code so the input prompt appears again
  1. Run MCP: List Servers from the Command Palette and confirm the orq server status is active
  2. Ensure GitHub Copilot is signed in and active
  3. Check network connectivity
  4. Review the server output log for error details