Angular MCP
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The Angular CLI includes an experimental Model Context Protocol (MCP) server enabling AI assistants in your development environment to interact with the Angular CLI. We've included support for CLI powered code generation, adding packages, and more.
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The Angular CLI includes a Model Context Protocol (MCP) server that enables AI assistants (like Cursor, Antigravity, JetBrains AI, etc.) to interact directly with the Angular CLI. It provides tools for code generation, workspace analysis, and running builds/tests.
Integration with Angular AI Agent Skills
If your host environment supports custom Agent Skills (such as Antigravity), you can combine the Angular CLI MCP server with the officialAngular AI Skills. While the skills provide the agent with deep instruction-level guidance and coding standards, the MCP server provides the action tools (like compiling, running tests, and analyzing workspaces) to execute those guidelines, resulting in a complete and powerful development agent.
To use the MCP server, you configure your host environment (IDE or CLI) to runnpx @angular/cli mcp.
When the MCP server is enabled, AI agents have access to the following tools:
These workflows demonstrate how AI assistants coordinate different MCP tools to automatically achieve complex developer stories.
1. Performance Tuning: Zoneless & OnPush Migration
The AI agent optimizes change detection performance and migrates components to a zoneless-ready state.
- Discover Workspace: The AI agent callslist_projectsto locate components, projects, and style/test configurations in the workspace.
- Schematic Modernization (Prerequisite): The AI agent runs any prerequisite signal migrations using standardng generatecommands (e.g., Signal Inputs, Signal Queries).
- Plan Migration: The AI agent callsonpush_zoneless_migrationwith the absolute path of the directory or component file.
- Apply Changes: The AI agent automatically applies the single actionable change returned by the tool to the codebase.
- Verify Changes: The AI agent runs unit tests by callingrun_targetwith the target parameter set to"test".
- Repeat: The AI agent callsonpush_zoneless_migrationagain to retrieve the next step, repeating until the tool indicates the migration is complete.
The AI agent automates research, implementation, and verification when developing new features.
- API & Syntax Research: The AI agent usessearch_documentationto look up Angular APIs or syntax rules (e.g.,@deferblock options).
- Load Coding Standards: The AI agent callsget_best_practiceswith the workspace path to load Angular version-aligned coding rules.
- Start Local Dev Server: The AI agent starts a background server by callingdevserver.start.
- Monitor Build: The AI agent usesdevserver.wait_for_buildto watch build logs and ensure compilation succeeds as it edits the code.
- Write and Execute Tests: The AI agent identifies the project's test framework (e.g., Jasmine, Jest, Vitest) vialist_projects, writes the corresponding test file, and runs the tests usingrun_targetwith"test".
- Stop Dev Server: When finished, the AI agent stops the active dev server by callingdevserver.stop.
The AI agent guides the developer through Angular concepts in an interactive sandbox.
- Discover Projects: The AI agent callslist_projectsto scan the workspace and identify the codebase structure.
- Launch Tutor: The AI agent runsai_tutorto load the curriculum instructions, persona, and tutoring guidelines.
- Follow the Curriculum: The AI agent guides the user through the curriculum, explaining concepts and instructing them on what components to build or modify.
- Implement & Verify: The AI agent helps implement the sandbox code and verifies changes usingrun_targetwith"test"or"build".
You can pass arguments to the MCP server in theargsarray of your configuration:
- --read-only: Only registers tools that do not modify the project.
- --local-only: Only registers tools that do not require an internet connection.
"args": ["-y", "@angular/cli", "mcp", "--read-only"]
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