Summary
Gateway
Server-Side MCP Execution (Beta)
MCP tools now work through the AI Gateway on any provider—including AWS Bedrock and Vertex AI, which don’t natively support remote MCP. The gateway handles fetching tool definitions and executing calls server-side, so you get MCP capabilities without any provider-level changes.OTel: Guardrail execution spans
Guardrail checks now emit their own OTel spans, so exactly what your guardrails did right alongside the model call in your traces.Token metering for MCP and agent requests
Every token from MCP requests and agent endpoints now shows up in your analytics and logs alongside LLM usage—one complete picture of consumption across all your AI workloads.MCP gateway: OTel log export
MCP traffic now appears in the same observability pipeline as your LLM workload exported to your OpenTelemetry collector alongside gateway logs.Guardrails
Alibaba Cloud AI
Alibaba Cloud AI is now available as a guardrail for content safety checks, configurable through the standard guardrails workflow.Models and providers
Azure AI Inference
- Image generation and editing now supported for MAI models (e.g., MAI-Image-2.5)
New providers
- MiniMax — chat completions
Anthropic
- Context management:
context_managementpassed through to the upstream API, enabling memory tools and managed-context workflows on Claude models - Claude Code OAuth: Requests from Claude Code using an OAuth bearer token now forward
Authorizationto Anthropic correctly - File downloads: Binary responses (e.g., PPTX from Skills + Code Execution) now pass through untouched
- Thinking blocks in streaming: Reasoning summary blocks are now included in streaming Responses API responses for Anthropic models
Bug fixes and improvements
- Vertex AI: MoonshotAI model provider now supported
- Modal: embeddings now supported alongside chat completions
- Fireworks AI:
stream_optionssupport added - Amazon Bedrock Guardrails now only block when the action is blocked
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