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Overview

Claude Code is Anthropic’s official CLI that brings Claude’s capabilities to your terminal and development workflow. With the Orq MCP integration, you can access all Orq.ai features directly through Claude Code’s conversational interface.

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Prerequisites

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Installation

Add the Orq MCP server to Claude Code with a single command: 
claude mcp add --transport http orq https://my.orq.ai/v2/mcp \
  --header "Authorization: Bearer ${ORQ_API_KEY}"
Make sure to set your ORQ_API_KEY environment variable before running the command:
export ORQ_API_KEY="your-api-key-here"

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Verify Installation

Check that the Orq MCP is installed: 
claude mcp list
You should see orq in the list of available MCP servers.

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Available Commands

Once integrated, you can ask Claude Code to perform these operations:
  • 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-id]
  • Add datapoints to dataset [dataset-id]
  • Update datapoint [datapoint-id]
  • Delete dataset [dataset-id]
  • Create an experiment from dataset [dataset-id]
  • List all experiment runs
  • Export experiment run [run-id] as CSV
  • Run experiment and auto-evaluate results
  • Create an LLM-as-a-Judge evaluator for tone
  • Create a Python evaluator to check response length
  • Add evaluator to experiment [experiment-id]
  • 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

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Usage Examples

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Create an Experiment

Create an experiment called "GPT-5.2 vs Claude Sonnet 4.6 Comparison" using the "customer-queries" dataset
Claude Code will:
  1. Use search_entities to find the “customer-queries” dataset
  2. Use create_experiment with the specified name and dataset ID
  3. Configure task columns with GPT-5.2 and Claude Sonnet 4.6 models
  4. Return the experiment ID and configuration details

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Query Trace Analytics

Has my system thrown any errors in the last 24 hours?
Claude Code will:
  1. Calculate the time range for the last 24 hours
  2. Use list_traces with error status filter
  3. Analyze the error data
  4. Provide a summary of total error count, error types and frequencies, affected traces, and time distribution

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Create a Synthetic Dataset

Create a dataset called "Product Questions" with 50 synthetic customer questions about e-commerce products
Claude Code will:
  1. Generate 50 synthetic customer questions about e-commerce products
  2. Use create_dataset to create a new dataset named “Product Questions”
  3. Use create_datapoints to add all 50 questions to the dataset
  4. Confirm creation with the dataset ID and summary

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Performance Analysis

Has my system's performance improved or decreased over the past week?
Claude Code will:
  1. Use query_analytics with a 7-day time range
  2. Analyze average latency trends over time
  3. Review token usage patterns and cost variations
  4. Compare error rate changes across the week
  5. Provide insights on model performance comparisons and trends

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Complete Experiment Creation

I have a CSV file with 100 customer queries. Create a dataset, add an LLM evaluator for tone and accuracy, then run an experiment comparing GPT-5.2 and Claude Sonnet 4.6
Claude Code will:
  1. Read and parse your CSV file
  2. Use create_dataset to create a new dataset with an auto-generated name
  3. Use create_datapoints to add all 100 customer queries from the CSV
  4. Use create_llm_eval to create an LLM-as-a-Judge evaluator for tone
  5. Use create_llm_eval again to create an LLM-as-a-Judge evaluator for accuracy
  6. Use create_experiment with the dataset ID and auto-run enabled
  7. Configure two task columns (one for GPT-5.2, one for Claude Sonnet 4.6)
  8. Execute the experiment automatically via the auto-run option
  9. Summarize the results with evaluation scores for both models

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Trace Investigation

Show me the 10 slowest traces from yesterday and explain what might be causing the latency
Claude Code will:
  1. Calculate yesterday’s date range
  2. Use list_traces with latency sorting (descending) and limit of 10
  3. Use list_spans to retrieve span information for each trace
  4. Analyze the execution patterns and span durations
  5. Provide performance insights identifying bottlenecks
  6. Suggest optimization opportunities based on the data

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Troubleshooting

  1. Verify your API key is valid: echo $ORQ_API_KEY
  2. Check the API key has the necessary permissions
  3. Re-add the MCP with the correct API key
  1. Verify the endpoint URL is correct
  2. Check your internet connection
  3. Try removing and re-adding the integration
  1. Get MCP server details: claude mcp get orq
  2. Verify the MCP is properly installed: claude mcp list