> ## Documentation Index > Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # 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!](https://github.com/Arize-ai/openinference/issues/new/choose) *** ## Integration Types Phoenix offers several types of integrations to support your AI development workflow: Integrate Phoenix with AI coding assistants like Claude Code and Cursor for debugging and analysis. Automatically capture traces from your AI applications built with popular frameworks and LLM providers. Use any LLM provider to power Phoenix's evaluation capabilities for scoring and classifying your traces. Integrate with external evaluation libraries like Ragas, Cleanlab, and MLflow to visualize results in Phoenix. Convert traces from other instrumentation libraries to the OpenInference format. Run code evaluators in hosted sandbox providers with kernel-level isolation. *** ## Developer Tools Integrate Phoenix with AI coding assistants to debug and analyze your LLM applications directly from your development environment. Install Phoenix debugging skills and CLI for Claude Code, Cursor, and other AI coding assistants. Connect AI assistants directly to your Phoenix instance via the Model Context Protocol. *** ## Tracing Integrations Phoenix captures detailed traces from your AI applications, giving you visibility into every step of your LLM pipeline. ### By Language ### LLM Providers Phoenix provides native tracing support for all major LLM providers: ### Platforms Integrate Phoenix with AI development platforms and infrastructure: *** ## 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. *** ## Eval Library Integrations Use external evaluation libraries alongside Phoenix to get the best of both worlds: *** ## Span Processors Normalize and convert data from other instrumentation libraries by adding span processors that unify traces to the OpenInference format: *** ## Sandboxes Run Phoenix [code evaluators](/docs/phoenix/evaluation/server-evals/code-evaluators) in hosted sandbox providers for kernel-level isolation, runtime dependency installation, and opt-in outbound network access. Configure providers from [Settings → Sandboxes](/docs/phoenix/settings/sandboxes).