Proxy Infrastructure for the Agentic Era
Your AI agents need reliable, authenticated web access. We built the infrastructure for exactly that.
AI agents interact with the web at a different cadence than human-driven pipelines: they make autonomous decisions about what to fetch and run multi-step workflows that need session continuity, often firing dozens of requests in a single reasoning cycle. That burst pattern gets datacenter IPs rate-limited or blocked fast. LocalProxies routes agent traffic through real residential connections instead, with sticky sessions that hold one IP across a multi-step workflow, high rotation for broad collection, and a single HTTPS or SOCKS5 endpoint that any proxy-capable framework can use. Give each agent its own port, authenticate by IP whitelist or username and password, and pay flat per-GB for the data your agents actually move.
How it works
One endpoint. Full control over geography, rotation, and session type.
Key capabilities
Built for this use case. No compromises.
Reliable Residential Access
Agents fire bursts of programmatic requests that datacenter IPs get rate-limited or blocked for almost immediately. Routing through real residential connections gives every request an authentic consumer-ISP origin, so your agents reach the same web a person would from that network.
Sticky or Rotating, Per Port
Use a Sticky port to hold one residential IP for 10 minutes or more across a multi-step workflow (login, pagination, extraction), or a High-Rotation port to get a fresh IP on every request for broad collection. Mode, country, and rotation are set per port.
One Endpoint, Any Framework
A single gateway over HTTPS or SOCKS5, authenticated by IP whitelist or username and password. Any agent framework that can use a proxy (LangChain, CrewAI, AutoGen, Claude tool-use) works with no custom SDK or integration code.
Why AI Agents Need Residential Proxies
AI agents interact with the web at a fundamentally different cadence than human-driven pipelines. An agent that decides to research a topic might issue dozens of requests in seconds (navigating search results, following links, extracting data from multiple pages) all within a single reasoning cycle. This burst pattern, combined with the repetitive structure of programmatic requests, triggers rate-limiting and access restrictions far faster than organic human browsing. Datacenter IPs compound the problem: their known hosting ASNs signal automated traffic before the first request even completes.
Residential proxies address this by routing agent traffic through real household internet connections. The requests carry authentic TLS fingerprints, originate from consumer ISP ranges, and blend with normal browsing patterns. This is not about disguising what the agent is doing. It is about ensuring the agent has the same quality of web access that a human researcher would have from that same network. For agents performing legitimate data collection, market research, or compliance monitoring, residential connections provide the reliable foundation that autonomous workflows require.
Sticky Sessions for Multi-Step Workflows
The most valuable agent workflows are not single-request operations. They are multi-step sequences: search for information, navigate to a result, extract data from a detail page, follow related links, compile findings. Each step depends on the previous one, and many web services expect sequential requests to originate from a consistent network identity. A proxy that rotates your IP mid-workflow breaks that continuity and forces the agent to restart, wasting tokens, bandwidth, and time.
A Sticky port holds the same residential IP for 10 minutes or more, so every request in a multi-step workflow keeps a consistent identity. Point the agent at that port and set the country and rotation interval in Port Options. For broad, stateless collection where IP diversity matters more than continuity, a High-Rotation port gives a new IP on every request instead. You can run both on one account: one agent holds a sticky session for deep research while another rotates for wide monitoring, neither interfering with the other.
Running Multiple Agents on One Account
Modern AI applications rarely deploy a single agent. They run teams: a research agent gathering data, an analysis agent processing it, a monitoring agent tracking changes. Each agent needs its own web access, and managing a separate proxy account per agent creates administrative overhead that defeats the purpose of autonomous operation.
A LocalProxies plan comes with multiple ports (Sticky) or threads (High-Rotation). Give each agent its own port and it gets an independent endpoint with its own session and rotation settings and its own whitelisted IP. Because billing is by total bandwidth rather than per agent or per seat, adding agents does not add a fixed cost: you pay only for the data your agents actually move. Whitelist each agent machine, or use a port username and password to connect from any IP.
Simple to Integrate, Predictable to Budget
For an agent, a proxy has to be trivial to wire up and predictable to pay for. Anything that needs a custom SDK, a management console, or a per-seat contract adds friction that autonomous systems are meant to remove.
LocalProxies is a standard HTTP and SOCKS5 proxy: point your client at the gateway on the assigned port, authenticate by whitelisting the agent IP or using the port credentials, and every request routes through a residential IP. Standard status codes (such as 407 when a credential is missing, or 429 when a per-minute limit is reached) let your client handle failures with ordinary retry-and-backoff logic. Pricing is flat per gigabyte, from $3.00/GB down to $2.10/GB at volume, with no per-request or per-agent fee, and top-ups from 10 GB to 1 TB cover busy months with unused gigabytes rolling over.
Residential vs Datacenter Proxies for AI Agents
How residential proxies compare to datacenter alternatives for this workflow.
| Feature | Residential Proxies | Datacenter Proxies |
|---|---|---|
| Multi-step workflow reliability | Agents maintain consistent session identity across search, navigation, and extraction sequences on authentic residential connections | Session continuity is fragile. Datacenter IPs are frequently recycled or reassigned, disrupting multi-step agent workflows |
| Rate limit exposure | Requests from consumer ISP ranges blend with organic traffic, reducing the rate at which agents trigger access restrictions | Known hosting ASNs trigger aggressive rate limiting, forcing agents into retry loops that waste tokens and bandwidth |
| Geo-targeted data quality | Agents collect data as it appears to real consumers in each market: accurate pricing, availability, and localized content | Geographic targeting is unreliable from datacenter ranges. Many sites serve default or restricted content to server IPs |
| Scaling to many agents | Each agent gets its own port drawing from a large residential pool, so concurrent agents do not compete for a small set of addresses | Limited IP diversity means many agents quickly exhaust available addresses, creating conflicts between concurrent agents |
| Handling failures | Standard status codes and a fresh IP on rotation make transient blocks easy to recover from with ordinary retry logic | Frequent blocks and recycled IPs force agents into retry loops that waste bandwidth |
| Connection authenticity | Traffic inherits authentic TLS fingerprints and HTTP profiles from real residential devices, with no spoofing required | Synthetic fingerprint profiles require constant maintenance as detection systems evolve, adding complexity to agent deployments |
Network coverage
Example requests
curl
# Auth = your whitelisted IP. Session and rotation are set per port in Port Options. curl --socks5-hostname gate.localproxies.com:PORT https://api.example.com/data -v
Python (Claude tool-use)
import anthropic, requests # SOCKS5 needs PySocks: pip install "requests[socks]"
# Auth = your whitelisted IP, no username or password. Give each agent its own port.
proxies = {
"http": "socks5h://gate.localproxies.com:PORT",
"https": "socks5h://gate.localproxies.com:PORT",
}
def web_fetch(url: str) -> str:
r = requests.get(url, proxies=proxies, timeout=15)
return r.text[:2000]
client = anthropic.Anthropic()
msg = client.messages.create(
model="claude-opus-4-7",
max_tokens=512,
tools=[{"name": "web_fetch", "description": "Fetch URL via residential proxy",
"input_schema": {"type":"object",
"properties":{"url":{"type":"string"}},
"required":["url"]}}],
messages=[{"role": "user",
"content": "Fetch https://example.com and summarize"}],
)
print(msg)
Getting Started with AI Agent Proxies
A workflow-specific guide to start collecting data with residential proxies.
Point your agent at the proxy
Add the LocalProxies gateway and your assigned port to the agent HTTP client, and either whitelist the agent IP in the dashboard or use the port username and password. HTTPS and SOCKS5 both work. Setup takes a few minutes.
Assign ports and a session strategy
Give each agent its own port. For multi-step workflows (research, extraction, monitoring), use a Sticky plan so the agent keeps a consistent IP across sequential requests. For broad data collection, use a High-Rotation plan. Set the country and rotation per port.
Whitelist and scale
Add each agent machine to the port Allowed IPs (your plan includes 4 to 25 whitelist IPs by tier), or use the port username and password to connect from any IP. Add more ports as you add agents.
Track usage in your dashboard
Monitor bandwidth usage and remaining balance in your members panel, and top up from 10 GB to 1 TB if a busy month runs over. Billing is by total bandwidth across the account, so there is nothing to reconcile per agent.
Frequently asked questions
Common questions about using LocalProxies for this workflow.
Which AI agent frameworks work with LocalProxies?
Any framework that can route HTTP requests through a proxy. That includes LangChain, CrewAI, AutoGen, Claude tool-use, GPT function calling, and custom code in any language. LocalProxies is a standard HTTP and SOCKS5 proxy, so you configure it the same way you would any proxy in your HTTP client. No custom SDK is required.
Can I run multiple agents on a single LocalProxies account?
Yes. Your plan includes multiple ports (or threads); give each agent its own port. Each port is an independent endpoint with its own session and rotation settings and its own whitelisted IP. There is no per-agent fee: you are billed for total bandwidth, so you can add agents without adding per-seat cost.
What happens when a request is blocked or rate-limited?
The proxy returns standard status codes your client can handle: 407 if a credential is missing, 429 if a per-minute limit is reached, and the status codes returned by the target site pass through. Your agent can apply ordinary retry-with-backoff logic, or use a High-Rotation port so the next attempt exits from a different residential IP.
How does session persistence work across multi-step workflows?
Use a Sticky port: every request through it routes through the same residential IP for 10 minutes or more. Set the country and rotation interval in Port Options. For stateless, high-volume collection, use a High-Rotation port that gives a new IP on every request instead.
How is pricing structured for agent workloads?
Flat per gigabyte, from $3.00/GB down to $2.10/GB at volume, with no per-request or per-agent fee. That fits agent traffic, which varies unpredictably: you pay for the data moved, not for idle capacity. Bandwidth top-ups from 10 GB to 1 TB cover busy months, and unused gigabytes roll over. For high-volume deployments, custom pricing is available.
Have more questions? Visit our FAQ or contact support.
Related use cases
Explore how other teams use residential proxies.
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