{"id":"andrewyng-aisuite","name":"aisuite","af_score":60.2,"security_score":58.0,"reliability_score":30.0,"what_it_does":"aisuite is a lightweight Python library that provides a unified, OpenAI-style chat completions interface across multiple LLM providers. It also offers tool-calling abstractions (manual tool handling and automatic multi-turn tool execution via max_turns) and supports Model Context Protocol (MCP) tools through an MCPClient or tool config. Providers are added via a plugin-style adapter architecture.","best_when":"You want a single Python codepath to call and tool-call across heterogeneous LLM providers, and you can manage provider credentials and any tool-side execution securely.","avoid_when":"You need explicit, provider-agnostic rate-limit/backoff semantics guaranteed by the library, or you require strong, documented security controls for tool execution and data handling beyond basic client configuration.","last_evaluated":"2026-03-29T13:20:26.124088+00:00","has_mcp":false,"has_api":false,"auth_methods":["Environment variables (e.g., OPENAI_API_KEY, ANTHROPIC_API_KEY)","Passing provider config to aisuite Client constructor"],"has_free_tier":false,"known_gotchas":["Automatic tool execution uses max_turns; ensure you bound and validate tool side effects because the library handles the loop, not your application.","When using MCP tools, tool security filters/prefixing are mentioned as existing for documentation, but enforcement details are not shown in the provided README excerpt.","Provider selection uses a model string format like <provider>:<model-name>; incorrect formatting may lead to runtime failures."],"error_quality":0.0}