Integrations

Connect Phoenix with your favorite AI frameworks, LLM providers, and tools

Phoenix integrates with the leading AI frameworks, LLM providers, and tools to provide seamless observability, evaluation, and debugging for your AI applications. Whether you’re building with Python, TypeScript, or Java, Phoenix has you covered.

Don’t see an integration you need? We’d love to hear from you!

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Integration Types

Phoenix offers several types of integrations to support your AI development workflow:

Developer Tools

Integrate Phoenix with AI coding assistants like Claude Code and Cursor for debugging and analysis.

Tracing Integrations

Automatically capture traces from your AI applications built with popular frameworks and LLM providers.

Eval Model Integrations

Use any LLM provider to power Phoenix’s evaluation capabilities for scoring and classifying your traces.

Eval Library Integrations

Integrate with external evaluation libraries like Ragas, Cleanlab, and MLflow to visualize results in Phoenix.

Span Processors

Convert traces from other instrumentation libraries to the OpenInference format.

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Developer Tools

Integrate Phoenix with AI coding assistants to debug and analyze your LLM applications directly from your development environment.

Coding Agents

Install Phoenix debugging skills and CLI for Claude Code, Cursor, and other AI coding assistants.

Phoenix MCP Server

Connect AI assistants directly to your Phoenix instance via the Model Context Protocol.

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Tracing Integrations

Phoenix captures detailed traces from your AI applications, giving you visibility into every step of your LLM pipeline.

By Language

Python

OpenAI Agents SDK

LangChain

LlamaIndex

LangGraph

CrewAI

AutoGen

DSPy

Haystack

Instructor

Guardrails AI

Pydantic AI

smolagents

Google ADK

Agno

BeeAI

Portkey

Graphite

NVIDIA

MCP

Agent Spec

TypeScript

Vercel AI SDK

LangChain.js

Mastra

BeeAI

Claude Agent SDK

MCP

Java

LangChain4j

Spring AI

Arconia

LLM Providers

Phoenix provides native tracing support for all major LLM providers:

OpenAI

Anthropic

Amazon Bedrock

Google

Groq

MistralAI

VertexAI

LiteLLM

OpenRouter

Platforms

Integrate Phoenix with AI development platforms and infrastructure:

Dify

Flowise

LangFlow

Prompt Flow

Envoy AI Gateway

LiteLLM Proxy

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Eval Model Integrations

Phoenix’s evaluation library (phoenix-evals) can use any LLM provider to power evaluations. These models score, classify, and analyze your traces.

OpenAI

Anthropic

Amazon Bedrock

Google Gemini

VertexAI

MistralAI

LiteLLM

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Eval Library Integrations

Use external evaluation libraries alongside Phoenix to get the best of both worlds:

Ragas

Cleanlab

Pydantic Evals

MLflow

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Span Processors

Normalize and convert data from other instrumentation libraries by adding span processors that unify traces to the OpenInference format:

OpenLIT

OpenLLMetry (Traceloop)