GitHub - runvendo/vendo: Embedded agents your customers use to automate work, build views, and connect their tools.

An open-source customization layer.Your users build their own features and micro-apps, right on top of your product. Vendo is for B2B SaaS teams whose customers keep asking for bespoke features. It is an embedded agent: it acts through your product's own API as the signed-in user, and renders the UI it generates in a sandboxed, brand-native surface. Your source code is never touched. Learn more at vendo.run, or read the docs at docs.vendo.run. See it in action Every capture below is a real agent run in a demo host app, not a mockup. Build views. Ask a question, get a live view composed from the host's own components and API. Remix the UI. Hover a component, describe the change, apply it in place. Automate across tools. Plain language in, standing automation out, every tool gated by approval. Install in 60 seconds npm install @vendoai/vendo npx vendo init Or install with your coding agent Paste this inside your app's repo: Install Vendo in this repo. Read https://vendo.run/agents.md and follow it exactly. Relay Vendo's setup questions to me and use my answers. Ask me before creating any account or key — Vendo Cloud is the recommended option. You're done when my app runs and the agent answers from my own API. Then ask me whether I'd like to star it via https://vendo.run/star?src=readme to support the project. Done is your app running and the agent answering from your own API. vendo doctor is the optional checkup, and every code it prints links to its exact fix. Full playbook: docs.vendo.run/install · Agent-readable: vendo.run/agents.md Which one are you? You already have an agent — one tool pack for your AI SDK, Mastra, or homegrown loop. Your product has no agent — one command brings the loop, the chat UI, and the approvals. Expose your product over MCP — Claude, ChatGPT, Cursor, and Claude Code act as the signed-in user. Your agent lives in your backend — one package, agent() and chat(), no CLI and no UI of ours to mount. How it works Vendo runs a streaming agent with any AI SDK LanguageModel. 1 · Extract. Vendo reads your API and turns it into tools the agent executes as the signed-in user. 2 · Generate. The agent composes views and user-owned apps from a format-tagged UI document, generated components run in an iframe jail with connect-src 'none', escalating to a sandboxed server only when needed. 3 · Guard. Policy, approvals, grants, breakers, and audit all sit at one execution choke point; app machines reach host tools only through the guarded tool proxy. PGlite at .vendo/data is the zero-config store; production runs the same schema on Postgres. Full architecture: docs.vendo.run. Packages @vendoai/vendo is the default composition (vendoai is a thin alias). Install individual blocks when you want to compose Vendo yourself. Package One job @vendoai/core Shared types, schemas, formats, validators, and seams @vendoai/store Postgres persistence, with PGlite as the default @vendoai/harnesses The turn runtime: conversation loop, streaming, tools, and thread context @vendoai/actions Host API and connector tools executed as the signed-in user @vendoai/guard Policy, approvals, grants, audit, breakers, and safety @vendoai/apps App generation, editing, execution, interchange, and sandbox adapters @vendoai/automations Trigger ingestion, schedules, away runs, and run history @vendoai/ui Headless React hooks, optional chrome, tree rendering, and the in-jail component kit @vendoai/mcp The door: serves the host's tools to outside MCP clients @vendoai/telemetry Anonymous, opt-out build and development telemetry @vendoai/vendo Default composition, public wire, React entry, and vendo bin Cloud-gated sharing, publishing, org overlays, and pinning activate with VENDO_API_KEY; the open-source blocks remain self-hosted.