Building your own CLI coding agent with Pydantic-AI
13 days ago
- #AI
- #Development
- #CLI
- CLI coding agents differ from chatbots or autocomplete tools by reading code, running tests, and updating codebases.
- Building a custom CLI coding agent allows for tailored solutions that fit specific project needs and development standards.
- The architecture includes a core AI model (Claude from Anthropic), Pydantic-AI framework, MCP servers, and a CLI interface.
- Key components like sandboxed Python execution, up-to-date library documentation, and AWS MCPs enhance functionality.
- Structured problem-solving and reasoning capabilities improve debugging and code analysis.
- Desktop Commander MCP server enables file system operations, terminal command execution, and interactive REPL sessions.
- The final system integrates multiple MCP servers for comprehensive development support, including testing, documentation, and cloud services.
- CLI agents represent a shift from AI as a writing assistant to a development partner, understanding project context and executing tasks.
- Building a custom agent provides insights into the future of collaborative software development with AI.