Is SBproxy a reverse proxy, an AI gateway, or a model server?

All three, from one binary. It terminates TLS and handles HTTP/1.1, HTTP/2, WebSocket, and gRPC like nginx or Envoy. It routes LLM traffic to 200+ hosted models across 72 providers with guardrails, budgets, and MCP federation. And it serves open-weight models on your own GPUs by supervising vLLM or llama.cpp underneath. One config file drives all of it, and the AI features sit on a runtime that was already a production-grade proxy.

SBproxy is the open-source enterprise gateway for API, MCP, and AI model traffic. Outbound, it routes to 200+ hosted models across 72 providers through one OpenAI-compatible endpoint, picking models by prompt difficulty and rerouting on live cost-per-success, and serves open-weight models on your own GPUs. Inbound, it gates the crawlers, signed agents, and MCP clients that hit your APIs, with controls like Pay Per Crawl and Web Bot Auth. Both directions share one policy of virtual keys, budgets, and guardrails. Underneath sits a production-grade reverse proxy running auth, TLS, WAF, rate limiting, transforms, and caching. Single static binary, Apache License 2.0.

Can SBproxy serve models on my own GPUs?

Yes, on any GPU. A provider whose entire body is a serve: block boots to a first token: SBproxy resolves the weights, fits an engine and quantization to your card (bigger cards take FP8, smaller ones fall back to an int4 GGUF), runs vLLM or llama.cpp as a supervised subprocess, and routes to it. Run sbproxy doctor first and it reports what the host can serve. Every governance plane, meaning virtual keys, budgets, guardrails, and the usage ledger, applies to the local model unchanged, and a hosted provider placed after the local lane catches overflow under policy.

How is SBproxy different from vLLM or Ollama?

vLLM and Ollama serve a model. SBproxy stands up the environment around it: the governed OpenAI-compatible endpoint, virtual keys, budgets, guardrails on prompt and response, failover to hosted providers, and a verifiable usage ledger. It runs vLLM or llama.cpp underneath as supervised engines, so you keep the engine and gain the gateway.

How is SBproxy different from Cloudflare Pay Per Crawl?

Cloudflare runs at its own edge. SBproxy runs in your VPC, region, Kubernetes cluster, or air-gapped environment. Pricing is tier-aware, per route, per shape, and per agent rather than domain-wide. Inbound monetization, agent identity, content negotiation, and outbound AI governance live on one policy graph instead of separate Cloudflare products. Settlement supports both x402 and Stripe MPP, and you can act as your own Merchant of Record.

How is SBproxy different from other AI gateways like LiteLLM, Helicone, Portkey, or Kong AI Gateway?

Most AI gateways stop at routing calls to hosted providers. SBproxy also serves the weights: the same binary runs open models on your GPUs and applies the same keys, budgets, and guardrails to local and hosted traffic alike. It is also a real reverse proxy underneath, so auth, WAF, and rate limiting ride along instead of needing a second gateway. Helicone is excellent for LLM observability. LiteLLM is a Python library that grew a server, and sbproxy config import-litellm converts its config in an afternoon. Kong is a traditional API gateway with AI bolt-ons. None of them serve the model.

Where does SBproxy sit in my stack?

At the network hop between your apps or agents and the models they call, and between inbound AI traffic and your APIs. SDK gateways live inside one app's code, hosted edges govern from someone else's network, and agent platforms ask you to build on them; SBproxy is standalone infrastructure that deploys like nginx, works under any agent framework or platform, and fronts any hosted provider or your own GPUs. It terminates TLS with certificates it issues and renews from Let's Encrypt, so the governed endpoint can face the public internet behind virtual keys you mint and revoke at runtime.

How does SBproxy handle API keys and state across a fleet of instances?

SBproxy ships a dynamic key plane. Mint, rotate, and revoke virtual keys at runtime through the admin API with no reload, and a revoke takes effect on the next request. Keys are hashed at rest with HMAC-SHA256 and a server pepper, and upstream provider credentials are sealed with AES-256-GCM. Across a fleet of replicas, a built-in mesh keeps the keys, budgets, and per-key rate counters coherent using SWIM gossip and CRDT counters, so the cluster coordinates itself without an external Redis. LiteLLM and most AI gateways need a separate Redis to share that state across instances.

Where does SBproxy deploy?

Single binary on a server, Kubernetes operator on a fleet, or air-gapped install on a regulated network. Same policy graph in every shape. No phone-home. No SaaS edge. Bring your own Stripe, your own SSO, your own observability, and your own audit sink. Suitable for EU, India, Saudi Arabia, US public sector, defense, healthcare, and finance workloads with sovereignty requirements.

Is SBproxy open source?

SBproxy is open source under the Apache License 2.0. Free for any use, including production and commercial, with no field-of-use restriction. Read every line on GitHub. Verify every binary.

What is Pay Per Crawl and how does SBproxy support it?

Pay Per Crawl is the pattern of charging AI crawlers for access to content using HTTP 402 Payment Required. SBproxy ships the ai_crawl_control policy: AI crawlers that arrive without a valid payment token receive a 402 response with a JSON challenge. The crawler retries with the issued token and the proxy validates it through a pluggable ledger. Settlement supports x402 stablecoin and Stripe MPP. Tokens can be priced per route, per shape, and per agent.

What is Web Bot Auth and how does SBproxy verify AI agents?

Web Bot Auth is the IETF pattern for verifying signed AI crawlers and agents. SBproxy implements it through the bot_auth provider. Agents sign each request with an Ed25519 key under RFC 9421 HTTP Message Signatures and advertise their key id in the Signature-Input header. The gateway looks up the matching public key in its directory and verifies the signature. Agents that pass come through. Everything else gets 401.

Does SBproxy support MCP?

Yes. SBproxy ships an MCP gateway that federates internal tools under one identity model. Authentication supports OAuth2 with DPoP, PKCE, and DCR. Federated servers can be wrapped from any OpenAPI service, with per-server prefix and RBAC. The same policy graph that governs API and AI traffic also governs MCP tool invocations.

What does SBproxy replace?

A hosted model router (OpenRouter), an LLM proxy (LiteLLM, Portkey, Helicone), the hand-rolled shim in front of vLLM or Ollama, a traditional API gateway (Kong, nginx, Envoy), a guardrails service, a bot management product, and a payment rail for crawlers (TollBit, Skyfire). One runtime instead of six vendors stitched together, one policy plane instead of six control planes, one audit log instead of six disconnected feeds.

How many AI providers does SBproxy support?

SBproxy reaches 200+ models behind one OpenAI-compatible API through 72 native providers, including OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Azure AI Foundry, Groq, Mistral, Cohere, Together AI, Fireworks, xAI Grok, OpenRouter, Cerebras, NVIDIA NIM, Databricks, Snowflake Cortex, IBM watsonx, and Oracle GenAI, plus the models it serves itself on your GPUs via vLLM or llama.cpp and external self-hosted runtimes like Ollama and TGI. Routing supports fallback chains, weighted, round-robin, latency-based, cost-optimized, and outcome-aware strategies.

Is SBproxy safe to run in front of production traffic?

SBproxy ships as a single static Rust binary. Releases are cut from tagged commits in a public repository on GitHub. Dependencies are pinned and checksummed in Cargo.lock. The runtime does not fetch code from a public package registry when it starts. The deployment shape matches nginx, HAProxy, and Envoy. Hot reload is supported without dropping connections.

Payments

Charge for API, AI, or content access: get paid before serving a request, price AI crawler traffic, and prove what was consumed.

Three separate things, easy to conflate

SBproxy ships three payment-adjacent features that answer different questions. Getting paid decides whether a request reaches your origin at all. Pricing AI crawler traffic is a policy that issues and redeems 402 challenges for automated readers. Metering proves how much was consumed after the fact, and settles nothing on its own. Each has its own reference page; this one says which to read first.

Getting paid: proxy.payments

Off unless configured, and Apache-2.0 like everything else. One rule sits above the rest: a request reaches the origin only after a durable, committed record says the payment settled. Verified is not settled. A timeout, an open circuit breaker, or a write with an unknown fate all stop the request short of the origin.

One settlement state machine covers four rails: x402, Payment HTTP Authentication (MPP), Stripe, and Lightning (Core Lightning or LND as alternative backends for the same rail, never both at once).

proxy:
  payments:
    rails:
      - type: x402
        network: base-sepolia
        pay_to: "0x..."
        price_usd: 0.001

Before you cluster this

A node that configures both proxy.payments and proxy.cluster refuses to start. Settlement runs on one node against one SQLite file today, and the mesh cannot hold that state. This is the most common way a payments rollout gets blocked in planning, so check it before you design around horizontal scaling.

Pricing AI crawler traffic: Pay Per Crawl

An AI crawler without a payment token gets a 402 challenge, pays out-of-band, and retries with a token that redeems once

A policy that decides which requests are payable and what they cost, specifically for AI crawler traffic. A crawler without a valid payment token gets a 402 with a JSON challenge, pays out-of-band, and retries with a token that redeems exactly once. This policy does not settle payments by itself: with proxy.payments configured, settlement takes over 402 issuance; without it, an in-memory or HTTP ledger redeems tokens on its own.

Proving what was consumed

Two ledgers, two different questions, neither one a payment:

Metering cuts a signed, hash-chained receipt for every request an attesting origin serves: who consumed, on which route, how many units, at what outcome. A buyer holding only your published key set can re-derive the whole chain and catch a tampered entry.
AI usage ledger does the same hash-chained, optionally Ed25519-signed treatment for completed LLM calls on an AI gateway origin.
Value ledger is a different kind of accounting: dollars saved by routing to a local or self-hosted model instead of a configured cloud reference price. This is savings reporting for an operator, not a buyer-facing receipt.

What is not shipped

L402 is design notes only. There is no macaroon primitive, no L402 issuer or verifier, and no invoice-provider seam in the codebase today. If you need Lightning payments now, the Lightning rail under proxy.payments is what actually ships.

Where to start

You are	Start with
Monetizing an API or AI endpoint for the first time	Payment settlement, then the clustering note before assuming horizontal scale
Charging for AI model access	The same settlement path on an AI gateway origin, plus the usage ledger for a provable spend record
Billing on consumption instead of gating access	Metering: a signed receipt chain a buyer can verify independently, distinct from settlement

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