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sandbaseai/sandbase-harness

⭐ 682 TypeScript added to this list on 2026-08-17 repository created 2026-07-11

SandBase Harness is a runtime layer for operating AI agents, aimed at the gap between a model SDK and a production deployment. Agent SDKs handle the model loop; what they do not provide is persistent sessions, tool governance, sandbox boundaries, credential handling, memory, auditability and a human-facing interface for inspecting what happened. Harness supplies those. It exposes a Claude Managed Agents-style /v1 API alongside a local console, and stores agents, sessions, environments, credential vaults, memory stores, files, skills and API keys in SQLite by default, with file and skill bytes kept in a workspace state directory. Generated code runs inside a sandbox, and four backends are offered: a local process, per-session Docker containers, Kubernetes via exec and copy, and a self-hosted worker queue. Sessions emit resumable server-sent events, so a long-running agent can be replayed and debugged after the fact rather than watched live, and the console shows the same history to a human reviewer. Tool access is governed through MCP toolsets, permission policies, built-in tools and skill packages, with approvals for sensitive calls. Model providers are pluggable — OpenAI, Anthropic and OpenAI-compatible endpoints — but a workspace commits to one active provider boundary, configured through a settings system with validation and both form and JSON editing. A bridge over MCP stdio lets the runtime be driven as a plugin from another harness, covering agents, sessions, streamed turns, artifacts and cancellation. It is written in TypeScript, requires Node 22 or newer, ships a TypeScript SDK, and is explicitly local-first: no hosted control plane is required and all state stays in the operator's infrastructure.

https://github.com/sandbaseai/sandbase-harness

agent-runtimesandboxsessionsmcpgovernanceauditself-hostedtypescript

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