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Overview

The Claude Web App (claude.ai) supports Model Context Protocol integrations, allowing you to access Orq.ai features directly in your Claude conversations without installing any software.

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Prerequisites

  • Claude Pro or Claude Team subscription
  • Active Orq.ai account
  • Orq.ai API key

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Installation

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Add Custom Connector

Requirements: Claude Pro, Max, Team, or Enterprise plan
  1. Navigate to claude.ai/settings/connectors
  2. Click Add custom connector at the bottom of the Connectors section
  3. Configure the Orq MCP:
    • Name: Orq.ai
    • URL: https://my.orq.ai/v2/mcp
  4. Click Advanced settings to add authentication:
    • Add a custom header: Authorization: Bearer YOUR_ORQ_API_KEY
  5. Replace YOUR_ORQ_API_KEY with your actual API key
  6. Click Add to save the connector
The connector will be available in all your Claude.ai conversations after adding it.

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Verify Installation

Start a new conversation and ask: 
Can you list the available models from Orq?
Claude will use the MCP integration to fetch and display your available AI models.

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Available Commands

You can ask Claude to perform these operations using natural language:
  • 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 Experiments

Create an experiment called "Model Comparison Test" using my "customer-queries" dataset.
Configure it with GPT-5.2 and Claude Sonnet 4.6, then run it.
Claude will:
  1. Use search_entities to find the “customer-queries” dataset
  2. Use create_experiment with the name “Model Comparison Test” and auto-run enabled
  3. Configure two task columns (one for GPT-5.2, one for Claude Sonnet 4.6)
  4. Execute both models against the dataset automatically via the auto-run option
  5. Provide a summary of the results with evaluation metrics

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Analyze Traces

Show me all errors from my Orq traces in the last 24 hours
Claude will:
  1. Calculate the time range for the last 24 hours
  2. Use list_traces with error status filter
  3. Analyze the trace data
  4. Provide error count and types, affected deployments, time distribution, and suggested fixes based on error patterns

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Generate Synthetic Datasets

Generate 100 realistic customer support conversations about a SaaS product
and create a dataset called "Support Training" in Orq
Claude will:
  1. Generate 100 realistic customer support conversation examples (questions and expected responses)
  2. Use create_dataset to create a new dataset named “Support Training”
  3. Use create_datapoints to add all 100 conversations to the dataset
  4. Confirm creation with the dataset ID and sample of generated data

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Performance Analysis

Has my system's performance improved over the last week?
Show latency trends and cost metrics from Orq analytics.
Claude will:
  1. Use query_analytics with a 7-day time range
  2. Analyze average latency changes over the week
  3. Review token usage patterns and cost trends
  4. Examine error rate fluctuations
  5. Compare performance across different models
  6. Provide a summary report with insights on whether performance has improved or decreased

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Troubleshooting

  1. Verify the MCP URL is correct
  2. Check your API key is valid and has permissions
  3. Try removing and re-adding the integration
  4. Clear browser cache and cookies
MCP operations over HTTP can take a few seconds:
  • Be patient with large dataset operations
  • Break complex workflows into smaller steps
  • Check Orq.ai service status
  1. Verify the MCP integration is active in Settings
  2. Try rephrasing your request
  3. Check the MCP tools list