AI Agent

peerd

peerd is the first AI agent harness native to the browser, allowing AI agents to drive tabs, run sandboxed compute, and share peer-to-peer with no backend.

What is peerd?

peerd is an open-source browser extension that runs AI agent loops directly in the browser. It reads and drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds over a peer-to-peer WebRTC network. BYOK to the model provider of your choice, with no backend, no telemetry, and no cloud component in the data path.

peerd vs Similar AI Tools

Pricing ModelFreeFree, FreemiumFreeFree
Free Credits
Key Features
  • In-browser AI agent loop with full tool integration
  • Sandboxed compute: WebVM (Linux), JS Notebooks, and App tabs
  • Peer-to-peer sharing via WebRTC (preview channel)
  • Multi-agent workflow with verification and self-healing
  • 50+ AI models auto-routed per agent
  • 1000+ OAuth2 app integrations
  • Seven breakable boxes covering OWASP Agentic Top-10 vulnerabilities
  • Three guided simulations for cascading failures, human-agent trust, and rogue agents
  • Network-isolated Docker containers for safe execution
  • Code-to-runtime reasoning across cloud, Git, and Kubernetes
  • Action-gate enforces read-only policy on every API call
  • Sandboxed JavaScript execution for concurrent research
Pros
  • Fully client-side – no backend dependency or data leaks
  • Supports multiple model providers (Anthropic, OpenRouter, Ollama)
  • Replaces 10+ separate tools with one platform
  • Multi-agent orchestration saves time and context switching
  • Covers full OWASP Agentic Top-10 in a realistic manner
  • Docker isolation prevents accidental damage
  • Read-only by construction prevents accidental writes
  • Evidence-backed verification cross-checks every finding
Cons
  • Experimental (0.x) – breaking changes likely
  • Requires manual setup and API keys
  • Free tier limited to 5,000 credits per month
  • May have a learning curve for complex workflows
  • Requires Docker and technical setup
  • Not for production use; only for lab environments
  • Requires an LLM API key, incurring token costs
  • Limited to read-only operations, cannot remediate
Best For
  • Developers exploring AI agents
  • Privacy-conscious users wanting local control
  • Marketing teams
  • Content creators
  • Security researchers focusing on AI agent vulnerabilities
  • Developers building MCP-based applications
  • Security engineers
  • DevOps teams

How to use peerd?

  1. 1Clone the repository from GitHub.
  2. 2Load the extension/ folder unpacked in Chrome (or Firefox) with Developer mode enabled.
  3. 3Click the peerd icon in the toolbar to open the side panel.
  4. 4On first run, create a local vault unlocked by Touch ID, passkey, or passphrase.
  5. 5Add your API key(s) for Anthropic, OpenRouter, or Ollama in Settings.
  6. 6Start chatting – peerd can read and drive open tabs, run commands in a sandboxed VM, build apps, and more.

peerd Key Features

  • In-browser AI agent loop with full tool integration
  • Sandboxed compute: WebVM (Linux), JS Notebooks, and App tabs
  • Peer-to-peer sharing via WebRTC (preview channel)
  • BYOK – bring your own API keys (Anthropic, OpenRouter, Ollama)
  • No backend, no telemetry, no cloud storage
  • Local encrypted vault for keys, chat history, and audit log
  • Voice input with local STT (Moonshine)
  • Open source under Apache 2.0

peerd Use Cases

  • Automating browser tasks and web scraping
  • Building and testing code in a sandboxed environment
  • Creating and running AI-powered apps
  • Collaborating with AI agents over a P2P network
  • Privacy-preserving AI agent experimentation

peerd Pricing & Free Credits

peerd currently operates on a Free model.

This tool is completely free to use

Open Source

Free

Apache 2.0 license; self-hosted extension with no usage limits. Requires own API keys for model access.

peerd Pros & Cons

Pros

  • Fully client-side – no backend dependency or data leaks
  • Supports multiple model providers (Anthropic, OpenRouter, Ollama)
  • Sandboxes code execution (WebVM, Notebook) for safety
  • P2P sharing enables decentralized agent collaboration
  • Strong security boundaries: vault, egress chokepoint, disposable runner

Cons

  • Experimental (0.x) – breaking changes likely
  • Requires manual setup and API keys
  • Limited to browser environment (Chrome/Firefox)
  • CheerpX VM depends on proprietary runtime (licensing restrictions for commercial use)

What is peerd best for?

  • Developers exploring AI agents
  • Privacy-conscious users wanting local control
  • Researchers testing agent workflows in the browser
  • Hobbyists building personal AI assistants

peerd FAQ

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