Agent-Assisted Setup

Use a coding agent to automatically add Phoenix tracing to your application.

Agent-Assisted Setup

The fastest way to add Phoenix tracing to your application. Paste a single URL into your coding agent and it handles everything — dependency installation, instrumentation, and configuration.

Get started — paste this into your coding agent:

Follow the instructions from https://raw.githubusercontent.com/Arize-ai/phoenix/main/docs/PROMPT.md and ask me questions as needed.

How it works

1. Paste the URL into any coding agent (Claude Code, Cursor, Windsurf, Copilot, etc.)
2. The agent analyzes your codebase — detects language, LLM providers, and frameworks
3. The agent proposes an instrumentation plan based on your stack
4. You approve, and the agent implements tracing with the right integrations

Supported stacks: Python, TypeScript/JavaScript, and Java — covering 30+ LLM providers, frameworks, and platforms. See the full integration list.

What the agent does

• Phase 1 (Analysis): Scans imports and dependency files to detect your LLM provider and framework, then proposes an instrumentation plan. No code changes.
• Phase 2 (Implementation): Installs dependencies, creates a centralized instrumentation module, and configures OpenTelemetry to send traces to Phoenix.

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Alternative: MCP and Skills

For persistent documentation access, direct Phoenix instance operations, and reusable agent skills beyond the initial tracing setup, see the Coding Agents guide.

CLI

Terminal access to traces, experiments, datasets, and prompts.

MCP

In-editor Phoenix documentation lookup and direct Phoenix instance operations.

Skills

Reusable instructions so agents apply Phoenix best practices consistently.

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IDE-Specific Instructions

Claude Code

In your Claude Code session, paste the PROMPT.md URL and ask the agent to follow the instructions.

For richer ongoing integration, add the Phoenix MCP server:

claude mcp add --transport http phoenix-docs https://arizeai-433a7140.mintlify.app/mcp

Cursor

Open Cursor’s AI chat panel. Paste the PROMPT.md URL and instruct the agent to add Phoenix tracing.

For richer ongoing integration, add to .cursor/mcp.json:

{
  "mcpServers": {
    "phoenix-docs": {
      "url": "https://arizeai-433a7140.mintlify.app/mcp"
    }
  }
}

VS Code (Copilot)

Open the Copilot chat panel. Paste the PROMPT.md URL and ask it to follow the instructions.

For richer ongoing integration, add to .vscode/mcp.json:

{
  "servers": {
    "phoenix-docs": {
      "url": "https://arizeai-433a7140.mintlify.app/mcp"
    }
  }
}

Windsurf

Open the Cascade panel. Paste the PROMPT.md URL and ask the agent to add Phoenix tracing.

For richer ongoing integration, add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "phoenix-docs": {
      "serverUrl": "https://arizeai-433a7140.mintlify.app/mcp"
    }
  }
}

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Validate Your Setup

After the agent finishes:

1. Run your application and trigger at least one LLM call
2. Open Phoenix UI (local: http://localhost:6006, or your Phoenix Cloud URL)
3. Navigate to the Traces view and verify traces appear under your project

If no traces appear, check the Troubleshooting FAQ.