The Infrastructure Layer
Your Agent Is Missing
Not a chatbot wrapper. Not a plugin host.
A real computer — purpose-built for AI Agents.
✗ Close your laptop → Agent dies instantly
✗ OAuth tokens expire → Re-login every session
✗ Context lost after 30-50 messages
✗ $200 burned in 2h — no cost guardrails
✗ 780+ exposed instances — zero auth
✗ Any email can prompt-inject your agent
✗ 3.7h/week re-explaining context to AI
✓ 24/7 cloud pod → Agent never dies
✓ Auth proxy → Tokens auto-refresh forever
✓ Persistent workspace → Picks up instantly
✓ Budget limits per session → No surprise bills
✓ Isolated VPS → Your data stays yours
✓ Sanitized I/O → Prompt injection mitigated
✓ Full audit trail → Every action logged
These aren't hypothetical problems.
They're what developers say every day.
"I let my AI agents run unsupervised and they burned $200 in 2 hours. The agent was still running. Making calls. Spending money. Just... going."
"780+ people deployed an AI agent with full system access to the public internet. No authentication. No IP filtering. Just... open."
"Tasks that should take ~1 hour take 5–6+ hours due to repeated mistakes. The agent simply stops following procedures it was using moments before."
"Agents often need broad local access: env vars, files, CLIs, browsers, API keys. This makes the usual assumption — 'the local machine is safe' — feel shaky."
"The current MCP spec focuses on tool interaction but leaves per-request authorization largely undefined. Relying solely on initial OAuth scopes falls short."
"Don't give the LLM any secrets at all — anything requiring escalated privilege should be done through a proxy which holds the credentials."
AgentPuter isn't just a feature list.
It plays five critical roles in your AI workflow.
Privacy Proxy
// Your data never leaves your control
You wouldn't paste banking credentials into ChatGPT. AgentPuter acts as a firewall between you and LLMs — sanitizing data, managing authorization, ensuring data ownership stays in your hands.
$ agentputer privacy status
Data flow: User → AgentPuter → [SANITIZED] → LLM
Credentials: encrypted at rest (AES-256)
API keys: managed, never exposed to models
PII detection: active, auto-redact enabled
✓ Your data stays yours
Context Manager
// Memory that never forgets
LLMs are amnesic. AgentPuter gives your agent long-term memory. It converts workflows, preferences, and file history into structured context — saving tokens while improving accuracy.
$ agentputer context show
Long-term memory: 847 entries
Preferences: 23 rules loaded
File history: 156 files tracked
Token savings: ~62% (smart context)
Last sync: 2m ago
✓ Picks up where you left off
Unified Interface
// One API for everything your agent needs
Every capability — documents, email, web, code — is wrapped as a standardized Tool. Agents call capabilities as naturally as a human uses a mouse, without learning each API.
$ agentputer tools list
├── documents (read, write, convert)
├── email (send, read, search)
├── web (browse, scrape, API)
├── calendar (events, reminders)
├── code (execute, test, deploy)
├── files (CRUD, organize)
└── custom (Skills marketplace)
✓ 7 core tools + unlimited Skills
Persistent Workspace
// Your agent's own desktop
The agent has its own file system, code repo, and research notes. Half-finished work is saved. Next session picks up exactly where the last one left off.
$ agentputer workspace status
~/workspace/
├── projects/ (3 active)
├── research/ (12 notes)
├── drafts/ (5 in progress)
└── exports/ (8 completed)
Storage: 2.1 GB / 40 GB
✓ Your agent's persistent home
Accountability Log
// Every action, recorded and reviewable
See exactly what your agent did, when, and why. Full decision chains logged. Sensitive actions auto-pause for human confirmation. Trust through transparency.
$ agentputer logs --last 5
[14:23:01] [agent] Received: 'compile sales report'
[14:23:02] [agent] Plan: fetch data → analyze → format
[14:23:05] [tool] Queried database: sales_q4_2025
[14:23:08] [agent] Generated report draft
[14:23:09] [⚠ CONFIRM] Send email to manager?
[14:23:15] [human] Approved ✓
✓ Human-in-the-loop for sensitive ops
What Can Your Agent Actually Do?
Office Work
"Compile last week's sales data, write a report, and email it to my manager." The agent pulls data, analyzes, formats, and sends — you just review.
Research
"Research 2025 EV market trends." Searches, reads, extracts key points, and produces a notebook — saved for follow-up.
Development
"Build a landing page for our product." Own dev environment. Writes code, runs tests, fixes bugs, deploys — asks you when stuck.
Creative
"Design a social media campaign for Q1." Own canvas and assets. Generates drafts, iterates, saves versions. You direct.
AgentPuter vs. Everything Else
$ agentputer compare --all Computer MCP / Agent- Dimension Use Plugins Claude OpenClaw Puter ───────────────────────────────────────────────────────────────── Persistence None Limited Limited Local ✓ Full 24/7 uptime No No No Manual ✓ Auto Auth mgmt None Vendor Vendor Manual ✓ Auto Multi-agent No No No No ✓ Yes Remote access Cloud Cloud Cloud No ✓ Yes Audit trail Partial None None Partial ✓ Full Cost control None None None None ✓ Yes Injection def. None None None None ✓ Proxy Privacy Cloud Cloud Cloud ✓ Local ✓ Local User barrier Low Medium Low High ✓ Low Result: AgentPuter ████████████████████ 10/10 ✓
How It All Connects
$ agentputer architecture --verbose ╔═══ USER ENTRY LAYER ═════════════════════════════════════╗ ║ Telegram │ WhatsApp │ Discord │ Web │ API │ Voice ║ ╚══════════════════════════╤════════════════════════════╝ │ ╔═══ ORCHESTRATION LAYER ═══╧══════════════════════════╗ ║ 🔒 Privacy Proxy │ 🧠 Context │ 📋 Audit Log ║ ║ Task Planner → Step Decomposer → Dispatcher ║ ╚══════════════════════════╤════════════════════════════╝ │ ╔═══ EXECUTION LAYER ══════╧══════════════════════════╗ ║ 📄 Docs │ 📧 Email │ 🌐 Web │ 💻 Code │ 📁 Files ║ ║ 🔌 Unified Interface → Skills Marketplace ║ ╚══════════════════════════╤════════════════════════════╝ │ ╔═══ PERSISTENCE LAYER ════╧══════════════════════════╗ ║ 💾 File System │ 🗄️ State DB │ 🔍 Vector Store ║ ║ All encrypted (AES-256) │ Local-first ║ ╚═══════════════════════════════════════════════════════╝
Ready to Give Your Agent
Its Own Computer?
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