SandBase Harness

SandBase Harness

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AI-readable project metadata: llms.txt · installation guide

A local-first runtime for AI agents. Sessions, sandboxed tools, memory, credentials, audit trails, and a built-in Console — all running on your machine or in your own infrastructure.

Why

Agent SDKs handle the model loop. Production agents need more: persistent sessions, tool governance, sandbox boundaries, credential handling, memory, auditability, and a UI for humans to inspect what happened. managed-agents is that runtime layer — not a visual workflow builder and not another model SDK.

Features

• Claude Managed Agents-style /v1 API and local Console
• SQLite metadata by default for agents, sessions, environments, credential vaults, memory stores, files, skills, and API keys — local file/skill bytes in the workspace state directory
• Resumable Server-Sent Events for session replay and debugging
• One active model provider boundary configured through Settings V2
• Sandbox backends: local process, Docker (per-session containers), Kubernetes (kubectl exec/cp), self-hosted worker queue
• MCP toolsets, permission policies, built-in tools, and skill packages
• TypeScript SDK at managed-agents/sdk
• Release gate: npm run release:check

Quick Start

Requirements: Node.js 22+, npm 10+, and a model provider API key (OpenAI, Anthropic, MiniMax, or any OpenAI-compatible endpoint). Docker is optional and only needed for Docker-backed sandboxes.

git clone --branch v0.3.8 --depth 1 https://github.com/sandbaseai/sandbase-harness.git

cd sandbase-harness npm ci npm run build mkdir ../my-agents && cd ../my-agents node ../sandbase-harness/dist/index.js init node ../sandbase-harness/dist/index.js start

init writes a workspace into the directory you run it from: an agent, a skills folder, and config.yaml, whose provider reference is the ${OPENAI_API_KEY} environment variable. start serves the API and the Console on http://127.0.0.1:3000.

Two steps finish the setup, both on Settings > Setup at http://127.0.0.1:3000/dashboard:

1. The provider. Paste your API key into the provider form and save. The page then reports that the saved configuration is not active yet, so restart the runtime — stop it with Ctrl+C and run the start command again, or use the restart button. A saved setting only takes effect at startup. If your provider is not in the list, choose the OpenAI-compatible vendor and set its base URL.
2. The model. In the Agent models panel, set the model ID your provider actually serves — deepseek-chat for DeepSeek, for example. An agent carries its own model ID, so the gpt-4o that init writes is not valid for every provider, and a wrong ID fails the turn with model_not_found.

Send the first message from the Console: open Sessions, create a session for the agent, and type into the composer. From a terminal it is one command:

node ../sandbase-harness/dist/index.js chat agent_assistant --message "hello" --tool-approval allow

chat sends that one message and exits once the turn settles; without --message it keeps the session open and streams until you interrupt it. --tool-approval allow preauthorizes the tool calls the agent may make, which the init template otherwise parks for approval and waits for a person to answer; see CLI.

The unscoped managed-agents name on npm is not this project. Until an official scoped package is announced in this repository, install only from the tagged GitHub source release shown above. Do not run npx managed-agents or npm install managed-agents.

Try it in Codespaces

The included development container installs dependencies and builds the runtime. When the terminal is ready, start the server on the forwarded port:

node dist/index.js start --host 0.0.0.0

Open the forwarded SandBase Harness Console port, then configure a model in Settings > Setup. Codespaces usage may be billed by GitHub; the local quick start above remains free and keeps all runtime data on your machine.

Screenshots

Use the Official SDK

The runtime answers its own /v1 API on that same port, and an official Anthropic TypeScript SDK client drives it unchanged: point the client's baseURL at the runtime, give it the runtime API key, and the quickstart in examples/official-sdk runs a whole turn — message, tool call, tool result, final reply — against it. That example is executed on every pull request by tests/conformance/official-sdk-quickstart.test.ts, so the compatibility it describes is compatibility that is tested rather than claimed.

The same surface is specified in docs/api.md, and this repository's own TypeScript SDK is documented under SDK below.

CMA compatibility

Coverage of the published Claude Managed Agents contract is declared entry by entry in src/core/capabilities/matrix.ts: of the official SDK's route surface (110 method/path pairs as of SDK 0.132.1), 90 routes are mounted and 20 refuse by name; no route is deferred. Partial and Unsupported entries always name their reason.

The table below is generated by npm run docs:compat, and a contract-honesty test fails when it drifts from the matrix.

Full compatibility table (generated)

| budget | session-budget | Partial | Consumption is priced in integer microcents from the append-only log, and a session may declare a max_list_cost ceiling at creation. The builtin loop checks the ceiling inside a turn: the step that crossed the cap is the last one, the session idles with stop_reason budget_reached and a session.usage immediately before it, and an accepted budget update or removal resumes the session on its own — a tool call the ceiling stranded is settled so the resumed turn sees a paired transcript. At the ceiling the next work-starting event is refused with budget_reached while events that settle work already in flight are still accepted, so the next model request does not start; a declared outcome's revision loop reads the same spend and stops at the ceiling too, closing the outcome with result budget_reached rather than starting another grading p