Code generation tools and MCP servers give AI agents specialized capabilities for writing, transforming, and understanding code. These go beyond basic autocomplete — providing full function generation, test scaffolding, documentation writing, refactoring suggestions, and multi-file code synthesis.

In the agent ecosystem, code generation tools often act as subagents within larger workflows. A higher-level orchestrator might delegate "write a unit test for this function" to a specialized code generation tool, then pass the result to a deployment tool. This composability is what makes agent frameworks powerful.

When comparing code generation tools, look at language support breadth, context window handling (can it work with large files?), and whether it integrates with your existing development environment. Tools that also handle linting and formatting post-generation save significant iteration time.