Vector Informatik GmbH, a developer of software-defined systems and engineering tools, has announced new AI and Model Context Protocol capabilities for its CANoe development and testing environment. With the new capabilities, engineers can automate complete workflows from requirements through test validation. Users can enter development, analysis and testing requirements as natural-language prompts. Specialized AI agents then determine and execute the required steps within CANoe.
CANoe becomes an AI-powered engineering assistant for development, testing and analysis. (Image courtesy of Vector Informatik GmbH)
MCP Server integration with CANoe, together with the CANoe AI Package, is available with CANoe Version 20 SP2. For automated test development, an engineer can provide a requirement through a single prompt, after which the AI agent can generate the corresponding CAPL test, execute it in CANoe, analyze detected errors, correct the CAPL code and rerun the test. The completed test scenario is then returned to the engineer for review and validation through synchronized CANoe windows before final approval. This approach keeps the engineer in control of test validation while allowing for the automation of repetitive development, debugging and execution steps. Users can determine the autonomy level assigned to individual agents and monitor each step within the development environment. Vector reports that, with these new capabilities, workflows that previously required hours or days can now be completed within minutes.
The CANoe AI Package uses an open ecosystem of AI agents, skills and MCP tools. Supported workflows include configuration access and modification, simulation control, test generation, communication-flow analysis and generation or optimization of CAPL, C# and Python code. Rather than requiring a Vector-specific language model, CANoe uses a user-supplied LLM, such as the LLM behind GitHub Copilot or Claude. Vector provides the AI integration layer consisting of agents, skills and MCP tools, which can also be extended with customer-specific components and domain knowledge. For technical grounding, Vector-RAG provides agents with access to a knowledge base containing relevant Vector documentation. The retrieval-augmented generation approach allows responses to draw from verified Vector technical information rather than relying solely on assumptions generated by the underlying language model. The architecture supports workflows ranging from individual engineering queries and test-generation tasks to more extensively orchestrated development, simulation, analysis and validation processes. The CANoe AI Package is available as a free download for CANoe 20 SP2 and later versions. It also requires a user-provided language model.
About Vector Informatik GmbH
Vector Informatik GmbH is a Stuttgart, Germany-based provider of software tools, embedded software, cloud services and engineering solutions for the development of software-defined systems. For more than 35 years, Vector has supported OEMs and suppliers in the development, testing and validation of complex electronic products, primarily for automotive applications and increasingly across medical technology, IoT, rail and aerospace. Its technology portfolio integrates development and testing tools, embedded software, cloud services and engineering expertise for systems requiring high levels of functionality, safety and efficiency. The independent company employs more than 4,500 people across 32 locations worldwide and generated more than €1 billion in revenue in 2024. For more information, please click here.
Source: Vector Informatik GmbH
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