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You’re using a coding agent — Cursor, Claude Code, Copilot, Windsurf, or something else — and you want it to know how to work with Arize AX. Here’s how:
  • Paste-and-Go — paste a single URL, agent does the rest
  • Skills — teach your agent the full Arize workflow: tracing, datasets, experiments, evals, prompt optimization, and more
  • MCP Servers — persistent IDE integration for instrumentation help and doc lookups
  • Copy Docs — paste any docs page as markdown into your agent for context

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Paste-and-Go Tracing Setup

The fastest path. Paste this into your coding agent and it handles dependency installation, instrumentation, and configuration:
Paste this into your coding agent:
Follow the instructions from https://arize.com/docs/PROMPT.md and ask me questions as needed.
The agent scans your codebase, detects your language and frameworks, proposes an instrumentation plan, and implements it once you approve. Supports Python, TypeScript/JavaScript, and Java across 30+ integrations. For more control, use the arize-instrumentation skill instead.

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Skills

Arize Skills encode the workflows we’ve refined building the Arize platform and helping teams debug LLM apps in production. They handle the ax CLI flags, data shape quirks, and multi-step recipes so your agent doesn’t have to guess. Your agent gets the full Arize workflow — add tracing, export traces, create datasets, run experiments, set up evaluators, manage annotations, optimize prompts — all through natural language. Works with Cursor, Claude Code, Codex, Windsurf, and 40+ other agents.
Already have traces? Give your agent this prompt to install skills and start debugging:
Install the Arize skills plugin from https://github.com/Arize-ai/arize-skills, then use the arize-trace skill to export and analyze recent traces from my project. Summarize any errors or latency issues you find.

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Prerequisites

  1. AX CLI: 
    uv tool install arize-ax-cli   # or: pipx install arize-ax-cli
  2. Authentication — set up your API key using one of these methods:
  3. Space ID — find yours in the Arize URL (/spaces/{SPACE_ID}/...) or run ax spaces list -o json.
  4. Verify: 
    ax --version && ax profiles show
See AX CLI overview for full details.

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Install Skills

Option 1: npx (recommended) 
# Interactive — choose skills, agent, and scope
npx skills add Arize-ai/arize-skills

# Non-interactive — install everything
npx skills add Arize-ai/arize-skills --skill '*' --yes
Option 2: git clone 
git clone https://github.com/Arize-ai/arize-skills.git
cd arize-skills
./install.sh --project ~/my-project
The installer auto-detects your agents and optionally installs the ax CLI. Use --global / -Global to install to ~/.<agent>/skills/. Run --list to see available skills, --uninstall to remove them. Updating skills: npx skills update or cd arize-skills && git pull.

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Available Skills

SkillWhat it does
arize-instrumentationAdd Arize AX tracing to an app — two-phase flow: analyze codebase, then implement instrumentation
arize-traceExport traces and spans by trace ID, span ID, or session ID; debug LLM application issues
arize-datasetCreate, manage, and download datasets and examples
arize-experimentRun and analyze experiments against datasets
arize-evaluatorCreate LLM-as-judge evaluators, run evaluation tasks, and set up continuous monitoring
arize-ai-provider-integrationCreate and manage LLM provider credentials (OpenAI, Anthropic, Azure, Bedrock, Vertex, and more)
arize-annotationCreate and manage annotation configs (categorical, continuous, freeform); bulk-annotate project spans
arize-prompt-optimizationOptimize prompts using trace data, experiments, and meta-prompting
arize-linkGenerate deep links to traces, spans, and sessions in the Arize UI

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MCP Servers

Two MCP servers you can plug into your IDE for persistent access to instrumentation guidance and documentation.
ServerBest forWhat it does
Tracing Assistant (PyPI)InstrumentationFramework-specific examples, code analysis, direct Arize support
Docs MCP ServerReferenceSearch all Arize AX docs, examples, and API references from your IDE

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Install uv

The Tracing Assistant requires uv (a fast Python package manager). The Docs Server needs no installation. 
pip install uv  # or: brew install uv

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Add to Your IDE

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Cursor

Navigate to Settings → MCP → Add new global MCP server, then add the JSON config: 
"arize-tracing-assistant": {
  "command": "uvx",
  "args": ["arize-tracing-assistant@latest"]
}

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Claude Code

claude mcp add arize-tracing-assistant uvx arize-tracing-assistant@latest
Verify with claude mcp list.

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Gemini CLI

gemini extensions install https://github.com/Arize-ai/arize-tracing-assistant

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Antigravity (Google)

Open the MCP Store panel (from the ... dropdown in the editor’s side panel), search “Arize”, and click Install. Alternatively, add the Tracing Assistant JSON config manually via Manage MCP Servers → View raw config.

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Claude Desktop / Manual Config

Add to your mcpServers JSON config (Settings → Developer → Edit Config in Claude Desktop): 
"arize-tracing-assistant": {
  "command": "uvx",
  "args": ["arize-tracing-assistant@latest"]
}
Troubleshooting: Run uv cache clean to reset cached versions, or start the server manually with uvx arize-tracing-assistant@latest to see errors. Debug with npx @modelcontextprotocol/inspector uvx arize-tracing-assistant@latest.

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Copy Docs to Your Agent

Every page in these docs has a copy as markdown button — paste it directly into ChatGPT, Claude, or any coding agent for accurate, up-to-date context.
Copy page button