We are excited to announce the release of Spring AI 1.0.0 Milestone 7. This will be the last milestone release. Next month will be the RC1 release followed quickly by a GA release in time for the Spring IO conference in Barcelona.

To celebrate this release, we have added a new song to our AI-generated music playlist featuring lyrics by Josh Long and Claude! Check out the latest track to enhance your blog reading and coding experience.

Here are the key changes in this release. Note, there are breaking changes!

Breaking Changes

Spring AI 1.0.0-M7 introduces several important changes that align…

This blog post is authored by Eddú Meléndez.

Docker recently released a Model Runner in Docker Desktop for Mac 4.40.0 on Apple silicon. The Docker Model Runner provides a local Inference API designed to be compatible with the OpenAI API, enabling easy integration with Spring AI as part of the Spring AI 1.0.0-M7 release. Models are distributed as standard OCI artifacts on Docker Hub under the ai namespace.

Prerequisites

• Download Docker Desktop for Mac 4.40.0.

• Choose one of the following options to enable the Model Runner:

  Option 1:

• Enable Model Runner `docker desktop enable model-runner --tcp 12434`.

• Set the base-url to `http://localhost:12434/engines\`

  Option 2:

• Enable Model Runner `docker desktop enable model-runner`.

• Use Testcontainers and set the base-url as follows:

…

On behalf of the community, I am pleased to announce that the Milestone 3 (M3) of the Spring Cloud 2025.0.0 Release Train is available today. The release can be found in Spring Milestone repository. You can check out the 2025.0.0 release notes for more information.

Notable Changes in the 2025.0.0 Release Train

A complete list of all changes in this release can be found in this project on GitHub.

The release is based off of Spring Boot 3.5.0-M3.

Spring Cloud Stream

• Add ability to define bindings dynamically with BindingsLifecycleController
• Add ability to modify existing binidngs with BindingsLifecycleController
• Fix SpEL Expresion serialization for Actuator
…

Hi, Spring fans! How are ya? I'm doing fine. Excited, even. You see, Spring AI M7 is coming soon! In theory, it drops on Thursday. Don't hold us to that — these things can change :-) But soon, and it's turning out to be a whopper of a release!

You should try upgrading your application to the new M7 by using the -SNAPSHOT builds. The coordinates for the various starters have been reworked, so things will break there. Don't panic — you just need to update the coordinates. There's good information in the documentation.

Here's the gist:

• Model starters: spring-ai-{model}-spring-boot-starter → spring-ai-starter-model-{model}
• Vector Store starters: spring-ai-{store}-store-spring-boot-starter → spring-ai-starter-vector-store-{store}
• MCP starters: spring-ai-mcp-{type}-spring-boot-starter → spring-ai-starter-mcp-{type}
…

On behalf of the team and everyone who has contributed, I am pleased to announce that the Spring Cloud Config 3.1.10, 4.0.10, 4.1.6, 4.2.1, 4.3.0-M3 are available now which fix CVE-2025-22232.

Spring Cloud Config 4.0.10 is a commercial only release and is not available in Maven Central.

Please refer to the releases page for more detail on what is included in each release.

On behalf of the team and everyone who has contributed, I'm happy to announce that Spring gRPC 0.6.0 has been released and is now available from Maven Central.

The main change in this release was to rename the annotation for creating gRPC client beans to @ImportGrpcClients, harmonizing with the work on HTTP interface clients in Spring Framework. This release includes features, bug fixes, documentation improvements, and dependency upgrades. Thanks to all those who have contributed with issue reports and pull requests.

How can you help?

If you're interested in helping out, check out the open issues. If you have general questions, please ask on Stack Overflow using the spring-grpc tag…

Hi, Spring fans! In this installment I talk to AWS Developer Advocate and industry legend James Ward about AWS Bedrock, Amazon Cohere, Spring AI, MCP, and so much more!

Using Spring AI 1.0.0-SNAPSHOT: Part 2 - Important Changes and Updates

This blog post is a continuation of our previous article Using Spring AI 1.0.0-SNAPSHOT: Important Changes and Updates, where we introduced the significant changes to artifact IDs, dependency management, and autoconfiguration in Spring AI 1.0.0-SNAPSHOT.

Since publishing that article, the Spring team has released an updates to the snapshots, In this follow-up article, we'll explore the latest changes and provide additional guidance for developers working with the snapshot versions. For comprehensive details, refer to the Spring AI Upgrade Notes…

Spring AI offers support for Model Context Protocol, or MCP for short, which allows AI models to interact with and access external tools and resources in a structured way. With Spring AI, developers can create their own MCP Servers and expose capabilities to AI models in just a few lines of code.

Authorization and security in MCP

MCP Servers can run locally, using the STDIO transport. To expose an MCP server to the outside world, it must expose a few standard HTTP endpoints. While MCP Servers used privately might not require strict authentication, enterprise deployments need robust security and permission management for exposed endpoints. This challenge is addressed in the newest version of the MCP specification (2025-03-26), which was released last week. It lays the foundation for securing communications between Clients and Servers, leveraging the widespread OAuth2 framework…