{"id":"aden-hive-hive","name":"hive","af_score":52.5,"security_score":48.2,"reliability_score":27.5,"what_it_does":"Hive is a Python runtime harness for AI agents in production. It supports goal-driven agent development (a coding “queen” generates an agent graph/code), then executes that graph with features like state isolation, checkpoint-based crash recovery, cost enforcement/degradation, real-time observability via streaming, and human-in-the-loop pause/intervention nodes. It also advertises integration through MCP tools and tool/agent SDK-wrapped nodes, with support for multiple LLM providers via LiteLLM-compatible interfaces.","best_when":"You need a self-hosted agent runtime that manages state, observability, recovery, and human oversight for production workloads.","avoid_when":"You only need lightweight experimentation without operational controls (recovery/cost/observability) or you require a turnkey hosted web API.","last_evaluated":"2026-03-29T14:20:42.702049+00:00","has_mcp":true,"has_api":false,"auth_methods":["API key / encrypted credential store (described as encrypted API key storage under ~/.hive/credentials)","LLM provider credentials (implied via provider configuration and LiteLLM-compatible setup)"],"has_free_tier":false,"known_gotchas":["Goal-driven code/graph generation implies agent behavior may vary across runs unless you pin configuration and model/versioning.","Human-in-the-loop pauses can affect throughput and require careful timeout/escalation configuration.","Browser control and tool execution can produce side effects; ensure idempotency at the tool/action layer if reruns occur after recovery."],"error_quality":0.0}