> ## Documentation Index > Fetch the complete documentation index at: https://docs.portkey.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # May **May-king it production ready✨** In May, we shipped the kind of upgrades that help you move your AI Agents fast into productiion and stay in control — whether you're scaling, securing AI behavior, or bringing new models to your apps. We launched deep integrations with agent frameworks like PydanticAI and OpenAI Agents SDK, added enterprise-grade controls to Claude Code, made it simpler to call a remote MCP server simpler and much more! Here’s everything new this month: ## Summary | Area | Key Highlights | | :--------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Platform** | • Full HTTP method support (`GET`, `PUT`, `DELETE`)
• OTel analytics export to your stack
• OpenAI Computer Use Tool support
• Multimodal embedding support (Vertex AI) | | **Enterprise** | • Deep Azure AI ecosystem integration (Foundry, APIM, Marketplace)
• Claude Code with enterprise controls (rate limits, observability)
• Model whitelist guardrail for org/env control | | **Integrations** | • Expanded AI Agent Frameworks (PydanticAI, OpenAI SDK, Strands)
• Support for latest models (Claude 4, Grok 3, Gemini 2.5) & new providers
• AI Coding Assistant integrations (Cline, Roo Code)
• Remote MCP server & Arize Phoenix tracing support | | **Security** | • New Prompt Security guardrails (injection, data protection)
• JWT validator input guardrail
• PANW Prisma AIRS plugin for real-time risk blocking | | **Resources** | • New Solution Pages (AWS Bedrock, GovCloud)
• New Cookbooks (OpenAI Computer Use, Llama Prompt Ops) | *** ## AI Agent Infrastructure AI agent frameworks are helping teams prototype faster, but taking agents to production requires real infrastructure. Portkey integrates with leading frameworks to bring interoperability, observability, reliability, and cost management to your agent workflows. PydanticAI is a Python framework that brings FastAPI-like ergonomics to building AI agents.

 OpenAI Agents SDK helps teams ship production-grade agents with built-in planning, memory, and tool use.

 Strands Agents is a lightweight agent framework built by AWS to simplify agent development.


 **Tracing Integrations: Arize AI** For teams consolidating observability into Arize, you can now view Portkey’s logs directly into Arize Phoenix to get unified trace views across your LLM workflows. ## Remote MCP servers Portkey now supports calling a remote MCP server that is maintained by developers and organizations across the internet that expose these tools to MCP clients via the Responses API Read more about the integration [here](https://portkey.ai/docs/product/ai-gateway/remote-mcp). ## Azure AI ecosystem More than half of Fortune 500 companies use Azure OpenAI. But building GenAI apps in the enterprise is still messy, cost attribution, routing logic, usage tracking, model evaluation... all scattered. With Portkey’s deep integration into the Azure AI ecosystem (OpenAI, Foundry, APIM, Marketplace), teams can now build, scale, and govern GenAI apps without leaving their existing cloud setup. Our customers are vouching for it! ## Portkey for AI Tools Bring enterprise-grade visibility, governance, and access control to Claude Code. Supercharge your AI-powered terminal with cost tracking, access controls, and observability. Add security, compliance, and real-time analytics to your code assistant workflows. Add essential enterprise controls to Goose's powerful autonomous coding capabilities ## Multilmodal embeddings Portkey now supports embedding APIs from Vertex AI for text, image, and video—across multiple languages. This unlocks the ability to: * Build multimodal search and retrieval * Power multimodal RAG pipelines * Track, route, and optimize embedding usage at scale Read more about the implementation [here](https://portkey.ai/docs/integrations/llms/vertex-ai/embeddings) ## Platform **Multi-label support for prompts** You can now assign multiple labels to a single prompt version, making it easy to promote a version across environments like staging and production. **Gateway to any API** Portkey now supports `GET`, `PUT`, and `DELETE` HTTP methods in addition to `POST`, allowing you to route requests to any external or self-hosted provider endpoint. This means you can connect to custom APIs directly through Portkey with full observability for every call. **OTel Integration (Analytics Data)** You can now export Portkey analytics to any OpenTelemetry (OTel)-compatible collector, integrating easily into your existing observability stack. **Improvements** * Token cost tracking is now available for `gpt-image-1`. * Ping messages are removed from streamed responses. * Resizing metadata columns in logs **This is what keeps us going!** ## New Models & Providers
## Guardrails * **Prompt Security guardrails**: Integrate with Prompt Security to detect prompt injection and prevent sensitive data exposure in both prompts and responses. * **JWT validator guardrail**: Added as an input guardrail to validate incoming JWT tokens before requests are sent to the LLM. * **PANW Prisma AIRS Plugin**: Portkey now integrates with Palo Alto Networks' AIRS (AI Runtime Security) to enforce guardrails that block risky prompts or model responses based on real-time security analysis. * **Model whitelist guardrail**: Restrict or deny specific models at the org, environment, or request level using a flexible whitelist/blacklist guardrail. **No frills. No hype. Just serious safety** ## Resources * Cookbook: [Optimizing Prompts with LLama Prompt Ops](https://portkey.ai/docs/guides/prompts/llama-prompts) * Cookbook: [OpenAI Computer Use Tool](https://portkey.ai/docs/guides/use-cases/openai-computer-use) * Guardrail documentation is now located under “Integrations”. * Expanded guides for agent frameworks, including CrewAI and LangGraph. ## Community Contributors A special thanks to our community contributors this month: * [unsync](https://github.com/unsync) * [tomukmatthews](https://github.com/tomukmatthews) * [jroberts2600](https://github.com/jroberts2600) ## Coming this month! Provision and manage LLM access across your entire org from a single admin panel. Centralized controls. Granular permissions. Stay tuned. ## Support Open an issue on GitHub Get support in our Discord