The open-source agent harness - the runtime layer that turns an LLM into a working agent
TrueForge
TrueForge runs the agent execution loop for you - model calls, MCP tools, skills, sandboxing, approvals, context management, and session state - and exposes it three ways: a chat UI, an HTTP API with a TypeScript SDK, and an embeddable UI SDK.

Why TrueForge?
Building an agent is easy. Running one well is not - you need streaming, session persistence, tool servers, sandboxing, approvals, and a UI. TrueForge gives you that out of the box:
- Initial setup from catalogs - configure models, MCP servers, skills, and a sandbox once; agents pick from what you connected. Presets come from shipped YAML catalogs you can customize.
- Any model provider - OpenAI, Anthropic, Google Gemini, and other catalog providers, or any OpenAI-compatible endpoint.
- MCP tools - remote MCP servers with header auth or OAuth, including in-chat authorization.
- Skills - git-backed
SKILL.mdinstruction packs, loaded on demand in the sandbox. - Sandbox as a tool - isolated code/file execution (Daytona today; more providers planned), provisioned only when needed. Secrets stay in the harness.
- **Hum