{"id":"maximerivest-mcp2py","name":"mcp2py","af_score":54.5,"security_score":50.8,"reliability_score":22.5,"what_it_does":"mcp2py turns MCP (Model Context Protocol) servers into Python modules by spawning/connecting to an MCP server and exposing MCP tools/resources/prompts as Python methods/attributes/template helpers. It also supports interactive server flows (elicitation), and can handle LLM sampling for servers using Anthropic/OpenAI via LiteLLM (or a custom sampling handler).","best_when":"You want to quickly wrap existing MCP servers (local subprocesses or remote endpoints) with Python ergonomics and type hints.","avoid_when":"You cannot accept automatic/interactive behaviors (OAuth browser login, terminal elicitation, or LLM sampling) without carefully disabling them or providing handlers/defaults.","last_evaluated":"2026-03-30T13:35:57.173109+00:00","has_mcp":false,"has_api":false,"auth_methods":["OAuth (via auth='oauth' example for MCP endpoints)","Static header-based auth (headers={'Authorization': 'Bearer ...'})"],"has_free_tier":false,"known_gotchas":["Server tools may be side-effecting; retry/idempotency guidance is not documented in the provided README","Automatic OAuth browser login and interactive terminal elicitation can block automated agents unless allow_elicitation/allow_sampling and handlers/defaults are explicitly configured","Sampling relies on environment variables or LiteLLM configuration; misconfiguration can cause failures when servers request LLM help","mcp2py loads/spawns MCP servers (including subprocess modes); sandboxing/permissions should be handled carefully, especially for filesystem-like servers"],"error_quality":0.0}