cli

Your AI coding assistant is smart, but it's trapped in a box. It can't search the web, check social media, generate images, or access real-time data — unless you wire up each API yourself.

SandBase changes that. One command connects your agent to 2,000+ AI models and APIs through the Model Context Protocol. No API keys to manage. No configuration headaches.

Building directly over HTTP instead of MCP? Start with the SandBase API quickstart or compare the unified LLM, image, and video API with specialized model gateways.

npx -y https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz connect

Or install the official Homebrew formula on macOS or Linux:

brew install sandbaseai/tap/sandbaseai-cli
sandbase connect

See the Homebrew launch announcement and macOS/Linux CI evidence.

For a reproducible install, verify the immutable release archive before running it. The SHA-256 for sandbaseai-cli-0.1.17.tgz is 1ad535b2899ca460b57b3c268aef278fee28fd28e649a89b92951514fd71fffa.

curl -fL -o sandbaseai-cli-0.1.17.tgz \
  https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz
echo '1ad535b2899ca460b57b3c268aef278fee28fd28e649a89b92951514fd71fffa  sandbaseai-cli-0.1.17.tgz' | shasum -a 256 -c -
npx -y ./sandbaseai-cli-0.1.17.tgz connect

Approve the browser authorization once; each supported client can then discover, inspect, and run available SandBase models and APIs through the local MCP bridge.

Want to inspect compatibility before signing in or changing configuration? The current v0.1.17 GitHub release includes a verified 25-client catalog:

npx -y https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz catalog --json

Homebrew users can run the same read-only check with sandbase catalog --json.

The npm latest tag currently serves v0.1.14 while tokenless trusted publishing is being enabled. The GitHub release tarball is built from the immutable v0.1.17 tag; its SHA-256 is published with the release.

Visit the official SandBase CLI project page for a compact overview. For a security-focused walkthrough of client detection, MCP tools, and rollback, read the 25-client SandBase CLI setup guide. AI agents and automated installers can use the concise llms-install.md instructions.

SandBase Open-Source Stack

• SandBase Harness — self-hosted agent runtime with persistent sessions, sandbox isolation, approvals, audit, and replay.
• SandBase Agent Skills — 88 installable Skills for research, social intelligence, marketing, and business workflows.
• SandBase for Codex — official Codex plugin packaging the SandBase MCP bridge and guided Agent Skill; its required HOL security scan passes on main.

Discover the authenticated remote bridge in the official MCP Registry, read its Registry community showcase, or find it through Chinese Independent Developer, Awesome MCP, Glama, TensorBlock MCP Index, MCPRepository, VaultPlane, AIMCP, MCP Server Hub, MCP Server Spot, or the Awesome AI API Proxy. External maintainers have merged SandBase into Awesome Codex CLI, Awesome Agent Skills, and Awesome MCP Server. The Hermes integration is independently listed in the Hermes Atlas ecosystem catalog and as beta in Awesome Hermes Agent. Install its verified sandbase Agent Skill from skills.sh, the sandbaseai/cli/sandbase listing on SkillsCat, the sandbaseai/cli/sandbase listing on skills.re, the 93/100 verified SandBase listing on vSkill, the security-audited SandBase listing on Skillstore, or the versioned sandbaseai/sandbase snapshot on Agent Skill Hub.

A Verifiable Agent Workflow

After connecting, ask your agent to follow the same inspectable sequence for search, data APIs, language models, image generation, video generation, and other catalog capabilities:

1. Use sandbase_discover to find candidates by task or capability.
2. Use sandbase_inspect to read the current input schema, pricing, and execution requirements.
3. Confirm the selected endpoint, parameters, and possible cost before calling sandbase_run.
4. For asynchronous work, use sandbase_run_get with the returned run_id instead of creating a duplicate run.
5. Use sandbase_runs to review recent run status and recorded cost.
6. Use sandbase_account to check the current account balance.

For example, start with a non-billable discovery request:

Find image models suitable for a square product illustration. Compare the required inputs and current pricing for the best two candidates. Do not run either model yet.

After reviewing the live response, explicitly approve the endpoint and inputs you want to run. Catalog entries, schemas, pricing, latency, and availability can change, so use the tool response from the current session rather than a static example.

See the complete Claude Code and Codex walkthrough or the Chinese workflow guide. For a live catalog example, read the GitHub connector discover-and-inspect dogfooding note.

What's Inside