The Phoenix client now includes the SpanQuery DSL, enabling more advanced and flexible span querying for distributed tracing and telemetry data. This allows users to perform complex queries on span data, improving trace analysis and debugging.

In addition, the get_spans_dataframe method has been migrated, offering an easy-to-use way to extract span-related information as a Pandas DataFrame. This simplifies data processing and visualization, making it easier to analyze trace data within Python-based environments.

Improvements and Bug Fixes 🐛

• Projects: Add "Copy Name" button to project menu

• TLS: Add independent flags for whether TLS is enabled for HTTP and gRPC servers

• Playground: Log playground subscription errors

• API: New RBAC primitives have been introduced for FastAPI and REST APIs

Phoenix now supports Transport Layer Security (TLS) for both HTTP and gRPC connections, enabling encrypted communication and optional mutual TLS (mTLS) authentication. This enhancement provides a more secure foundation for production deployments.

Highlights:

• Secure HTTP & gRPC Connections: Phoenix can now serve over HTTPS and secure gRPC.

• Flexible TLS Configuration: TLS settings are managed via environment variables.

• Optional Client Verification: Support for mTLS with configurable client certificate validation.

• Improved Testing: TLS-aware infrastructure added to integration tests.

• Better Visibility: Server startup logs now display TLS status.

Configuration Options

Set the following environment variables to enable and customize TLS:

Phoenix now supports programmatic API key creation through a new endpoint, making it easier to automate project setup and trace logging. To enable this, set the PHOENIX_ADMIN_SECRET environment variable in your deployment.

Improvements and Bug Fixes 🐛

• Tracing: Add load more and loading state to the infinite scroll

• UI: Hide menu for changing role for self in UsersTable

• Security: Prevent admins from changing their own roles

• Infrastructure: Remove WebSocket dependency and migrate to Multipart Subscriptions

We’ve added support for Prompt Tagging in the Phoenix client. This new feature gives you more control and visibility over your prompts throughout the development lifecycle.

• Tag prompts directly in your code and see those tags reflected in the Phoenix UI.

• Label prompt versions as development, staging, or production — or define your own custom tags.

• Add tag descriptions to provide additional context or list out all tags.

Check out documentation on prompt tags.

Improvements and Bug Fixes 🐛

• Infrastructure: Add aiohttp to container for azure-identity

The new span aside moves the Span Annotation editor into a dedicated panel, providing a clearer view for adding annotations and enhancing customization of your setup. Read this documentation to learn how annotations can be used.

Improvements and Bug Fixes 🐛

• Enhancement: Allow the option to have no configured working directory when using Postgres

• Performance: Cache project table results when toggling the details slide-over for improved performance

• UI: Add chat and message components for note-taking

Improved trace navigation by automatically scrolling the selected span into view when a user navigates to a specific trace. This enhancement eliminates the need for manual searching or scrolling, allowing users to immediately focus on the span of interest. It's especially useful when navigating from links or alerts that point to a specific span, improving debugging efficiency. This change contributes to a smoother and more intuitive trace exploration experience.

Improvements and Bug Fixes 🐛

• : Add /readyz endpoint to confirm database connectivity

• : Allow scroll on settings page

Newly added to the OpenAI Agent SDK is support for MCP Span Info, allowing for the tracing and extraction of useful information about MCP tool listings. Use the Phoenix OpenAI Agents SDK for powerful agent tracing.

This update enhances the Project Management API with more flexible project identification:

• Enhanced project identification: Added support for identifying projects by both ID and hex-encoded name and introduced a new _get_project_by_identifier helper function

Also includes streamlined operations, better validation & error handling, and expanded test coverage.

Improvements and Bug Fixes 🐛

• Performance: Restore streaming

• Playground: update Gemini models

• Enhancement: Route user to forgot-password page in welcome email url

This release introduces a REST API for managing projects, complete with full CRUD functionality and access control. Key features include:

• CRUD Operations: Create, read, update, and delete projects via the new API endpoints.

• Role-Based Access Control:

  • Admins can create, read, update, and delete projects

  • Members can create and read projects, but cannot modify or delete them.

• Additional Safeguards: Immutable Project Names, Default Project Protection, Comprehensive Integration Tests

Check out our new documentation to test these features.

Improvements and Bug Fixes 🐛

• Phoenix Server: add PHOENIX_ALLOWED_ORIGINS env

• Tracing: Delete annotations in the feedback table, Make feedback table scrollable

• Experiments: Allow scrolling the entire experiment compare table

• Projects: Make time range selector more accessible

• Playground: Don't close model settings dialog when picking Azure version

• Session: improve PostgreSQL error message in launch_app

When stopping the Phoenix server via Ctrl+C, the shutdown process now exits cleanly without displaying a traceback or returning a non-zero exit code. Previously, a KeyboardInterrupt and CancelledError traceback could appear, ending the process with status code 130. The server now swallows the interrupt for a smoother shutdown experience, exiting with code 0 by default to reflect intentional termination.

Improvements and Bug Fixes 🐛

• Fix: Use Float for token count summaries

• Enhancement: Improve browser compatibility for table sizing

• UX: Simplify homeLoaderQuery to prevent idle timeout errors

Tool call and result IDs are now shown in the span details view. Each ID is placed within a collapsible header and can be easily copied. This update also supports spans with multiple tool calls. Get started with tracing your tool calls .

Improvements and Bug Fixes 🐛

• Performance: Do not refetch tables when trace and span details closed

• UI: Redirect /v1/traces to root path

• Playground: Update GPT-4.1 models in Playground

We’re excited to announce a powerful capability in the OSS library openinference-instrumentation-mcp — seamless OTEL context propagation for MCP clients and servers.

What’s New?

This release introduces automatic distributed tracing for Anthropic’s Model Context Protocol (MCP). Using OpenTelemetry, you can now:

• Propagate context across MCP client-server boundaries

• Generate end-to-end traces of your AI system across services and languages

• Gain full visibility into how models access and use external context

The openinference-instrumentation-mcp package handles this for you by:

• Creating spans for MCP client operations

• Injecting trace context into MCP requests

• Extracting and continuing the trace context on the server

• Associating the context with OTEL spans on the server side

Set up

1. Instrument both MCP client and server with OpenTelemetry.

2. Add the openinference-instrumentation-mcp package.

3. Spans will propagate across services, appearing as a single connected trace in Phoenix.

Full example usage is available:

Walkthrough Video

Acknowledgments

Big thanks to Adrian Cole and Anuraag Agrawal for their contributions to this feature.