OpenHarness

Pi Agent Harness packages a unified multi-provider LLM API, a tool-calling runtime with state management, an interactive coding CLI, and a terminal UI as composable modules. It gives developers separate extension points for models, tools, and interfaces. Pi has no built-in permission system and inherits the launching process’s filesystem, network, and credential access, so stronger boundaries require a container or sandbox.

Deep Agents is an agent harness for long-running, multi-step work, with built-in planning, sub-agents, filesystem access, shell use, and persistence. Each part can be overridden or replaced without forking, and the framework can work with tool-calling frontier, open-weight, or local models.

Hive turns an objective into a graph-based runtime that coordinates specialized agents in parallel while preserving role memory, checkpoints, and execution state. It adds human-in-the-loop controls, observability, cost limits, browser and compute tools, and LiteLLM-compatible hosted or local models; teams building only simple one-off chains may not need this heavier harness.

TaskingAI is a backend platform for developing and deploying LLM-based agents. It brings models from multiple providers, tools, RAG systems, assistants, and conversation history under one console and unified API. Developers can prototype configurations in the UI, then integrate them into multi-tenant products through REST endpoints or the Python SDK. The community edition can be self-hosted with Docker Compose and requires configuration for the selected model services.