tierproxy

tierproxy — Python SDK

🚧 Preview release. Gateway is not yet generally available. Join the

waitlist at hello@tierproxy.com. SDK is functional but tierproxy doctor

against a live gateway requires invitation.

Premium multi-provider proxy infrastructure for AI/ML pipelines. Built for engineers who measure cost, latency, and success rate twice — and write Python.

Install

pip install tierproxy

Quickstart — five-second flavor

import tierproxy

r = tierproxy.get("https://example.com", country="US") print(r.text)

That's it. (Set TIERPROXY_API_KEY env var first.)

Three lines, persistent session

from tierproxy import TierProxy

with TierProxy() as g: print(g.me.get().client_id) r = g.get("https://example.com", country="US", session_id="s1")

Auto-pick the cheapest healthy upstream every request

g = TierProxy(routing="cheapest")  # also: "fastest", "most_reliable", "balanced"

g.get("https://example.com") # picks via /v1/health/upstreams under the hood

Cost guardrails

g = TierProxy(

monthly_budget_usd=200.0, # raises BudgetExceededError before going over )

Power-user knobs

import httpx

from tierproxy import TierProxy from tierproxy.retry import RetryPolicy

g = TierProxy( api_key="tp_live_...", base_url="https://my-self-hosted-gw:8444", timeout=10.0, retry_policy=RetryPolicy(max_retries=5, retry_on_status=frozenset({500, 502})), http_client=httpx.Client(verify=False), # custom transport user_agent_suffix="my-app/2.3", # attribution )

Raw modes (Playwright, curl, etc.)

from tierproxy import ProxyURL

p = ProxyURL(api_key="tp_live_...", country="US", mode="username_encoding") print(p.http_url()) # http://customer-tp_live_...-cc-US:x@gw.tierproxy.com:443

Error handling

Every SDK error inherits from tierproxy.TierProxyError and carries a request_id for support escalation:

from tierproxy import TierProxy, RateLimitError

import time

with TierProxy() as g: try: resp = g.get("https://example.com/page") except RateLimitError as e: time.sleep(e.retry_after or 5) resp = g.get("https://example.com/page")

See Errors reference for the full HTTP-status-to-exception mapping.

AI agent integration

The SDK exposes its response models as JSON Schema and as pre-built tool definitions for Anthropic Claude and OpenAI function-calling:

import anthropic

from tierproxy import TierProxy, schemas

with TierProxy() as gw: anthropic.Anthropic().messages.create( model="claude-sonnet-4-6", max_tokens=1024, tools=schemas.anthropic_tools(), messages=[{"role": "user", "content": "How much quota is left?"}], )

See the AI integration guide and the MCP server in examples/mcp_claude_desktop.md.

How tierproxy compares

Features

• Five-second quickstart — import tierproxy; tierproxy.get(url, country="US")
• Layered API — five integration levels from one-liner to power-user knobs
• Smart routing — routing="cheapest" auto-picks healthy upstream per request
• Cost guardrails — monthly_budget_usd= refuses requests that would exceed budget
• Per-request cost attribution — client.cost_for(resp) returns USD; lazy 30s cache, no per-request overhead
• Client-side response caching — cache_ttl=300, cache_max_response_size=262144 LRU with size cap
• Multi-provider auto-failover — auto_failover=True retries with next-best upstream on 429/5xx
• Rate-limit learning — client.rate_limits.get() surfaces gateway-aggregated 429s per target domain
• JA3/JA4 TLS rotation — per-upstream fingerprint randomization (gateway side; see tls-fingerprint guide)
• Cookie persistence — cookies stick to session_id across multi-step crawls
• Streaming responses — client.get(url, stream=True) returns iterator (large files, SSE)
• Live SSE stream — for delta in g.usage.stream() tails month-to-date bytes
• MCP server — tierproxy-mcp exposes proxy as tools to Claude/Cursor/Cline
• 8 framework integrations — LangChain, LlamaIndex, Crawl4AI, Playwright, Firecrawl, Browser-Use, CrewAI
• OpenTelemetry opt-in — pip install tierproxy[otel] for distributed tracing
• Geo + sticky sessions — countries, cities, 1-1440min session pins
• Dual URL syntax — headers (httpx/requests) AND username-encoding (Playwright)
• Type-safe end-to-end — Pydantic v2 models, mypy strict, full IDE autocomplete

See examples/ for LangChain/LlamaIndex/Crawl4AI/Playwright and examples/levels.py for a runnable demo of every level.

Use with your favorite AI/agent framework

MCP server (Claude Desktop / Cursor / Cline / Windsurf)

pip install tierproxy[mcp]

Then add to your MCP client config:

{

"mcpServers": { "tierproxy": { "command": "tierproxy-mcp", "env": { "TIERPROXY_API_KEY": "tp_live_..." } } } }

Now your AI assistant can call fetch_url(url, country="US"), inspect health and usage, and route through the cheapest healthy upstream — no glue code, no httpx imports, no boilerplate.