Proxies for AI Agents

Why AI agents need proxies at all

An AI agent is not a one-shot scraper. It reasons, plans, and acts in a loop: open a page, read it, decide, click, submit, and repeat, sometimes for dozens of steps against the same site. That long-lived behavior is exactly what breaks under a naive proxy setup. If the IP changes mid-task, the target site sees a session that suddenly teleported across the country, drops the login, and challenges the agent with a CAPTCHA or a hard block. The agent stalls, retries, and burns tokens trying to recover a state it can no longer reach. Routing agents through the right kind of proxy is what keeps the loop alive long enough to finish the job.

Sticky sessions preserve context and logins

For any workflow where an agent authenticates and then does work behind that login, the cardinal rule is one IP for the whole task. Our sticky proxies assign a stable IP to a session and hold it, so cookies, CSRF tokens and server-side session state all stay valid from step one to the final action. That is what lets an agent log into a portal, navigate three pages deep, fill a multi-step form, and submit it without being logged out or re-challenged. Sticky sessions are the difference between an agent that completes a booking, a checkout, or an account action and one that loops forever on a login wall.

Rotating IPs isolate parallel agents

The other half of agent infrastructure is scale. When you fan out a swarm of agents to research, compare, or monitor in parallel, you do not want them sharing one IP, because a rate limit or a block triggered by one agent then cascades to all of them. Give each agent its own IP from our rotating proxies and the failures stay isolated: one agent gets challenged, the other forty keep running. This rotating-plus-sticky split, sticky within a task and rotating across tasks, is the pattern that makes a proxy network genuinely practical for agentic workloads rather than just bulk crawling.

Anti-bot evasion for agents on protected sites

Modern sites fingerprint far more than the IP, but the IP is still the first gate. Datacenter ranges are widely flagged, so an agent that needs to operate on a heavily protected target, a social platform, a marketplace, a ticketing or booking site, should ride on residential or mobile IPs that present as real home and carrier connections. Combine that with sticky behavior and city-level targeting and the agent looks like a single consistent human user rather than a bot hopping networks. Match the proxy type to the target: datacenter for high-volume public pages, residential or mobile for the sources that block bots.

Built for MCP, LangChain and Playwright

You do not need a special SDK. Because the gateway speaks standard HTTPS and SOCKS5, it slots into the tools agents already use. Expose it as a network setting in an MCP server so any Model Context Protocol tool routes through it, wire it into a LangChain or LangGraph tool that fetches pages, or pass it as the proxy option to a Playwright or Puppeteer browser context that an agent drives. Point your tool at one endpoint with a host, port and credentials and your agents are running on a 100M+ pool. See the rotating proxy API for connection details, or compare the broader proxies for AI use case for training-data collection.