# AISIX AI Gateway **Category:** 💻 Developer Tools **Repository:** https://github.com/api7/aisix **Views:** 0 **Installs:** 0 **Upvotes:** 0 **Directory Page:** https://allmcps.com/mcp/aisix-ai-gateway ## Description Self-hosted AI gateway that governs MCP servers, LLM traffic, and A2A agents behind one endpoint ## Claude Desktop Quick Installation Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low): ```json "mcpServers": { "aisix-ai-gateway": { "command": "npx", "args": ["-y","aisix-ai-gateway"] } } ``` ## Documentation & README

# AISIX AI Gateway ### The open-source, Rust-native AI gateway for LLMs and AI agents **One OpenAI-compatible API in front of every model.** Route, govern, secure, cache, and observe all your LLM and AI-agent traffic from a single control point — shipped as one static binary with low per-request overhead. Run it in your infrastructure for free, forever. *Built by the original creators of [Apache APISIX](https://apisix.apache.org/).* [![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE) [![Built with Rust](https://img.shields.io/badge/Built%20with-Rust-orange.svg)](https://www.rust-lang.org/) [![Docs](https://img.shields.io/badge/docs-read-3aa757.svg)](https://docs.api7.ai/ai-gateway/) [![Discord](https://img.shields.io/badge/Discord-join-5865F2.svg)](https://discord.gg/dUmRZ7Rvf) [![Website](https://img.shields.io/badge/website-api7.ai-1a73e8.svg)](https://api7.ai/ai-gateway) [**Start free**](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=ai-gateway) · [**Documentation**](https://docs.api7.ai/ai-gateway/) · [**Quickstart**](https://docs.api7.ai/ai-gateway/getting-started/gateway-quickstart) · [**AISIX Cloud**](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=cloud) · [**Roadmap**](https://github.com/api7/aisix/blob/HEAD/ROADMAP.md)
AISIX AI Gateway architecture — one OpenAI- or Anthropic-compatible API in front of OpenAI, Anthropic, Gemini/Vertex, Bedrock, Azure OpenAI, and DeepSeek, with API key auth, rate and token limits, guardrails, caching, routing and failover, and observability in between

AISIX AI Gateway architecture — one OpenAI- or Anthropic-compatible API in front of OpenAI, Anthropic, Gemini/Vertex, Bedrock, Azure OpenAI, and DeepSeek, with API key auth, rate and token limits, guardrails, caching, routing and failover, and observability in between

--- **AISIX AI Gateway** is a Rust-native gateway that puts a single, OpenAI-compatible API in front of every LLM provider — OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, DeepSeek, and any OpenAI-compatible endpoint. It gives platform teams one place to route, govern, secure, and observe LLM traffic, with first-class SSE streaming and low gateway overhead. It runs as a **single static binary** — low cold-start, lock-free config reads, and hot configuration reloads with no restarts: declare resources in one `resources.yaml` and reload on `SIGHUP`, or point the gateway at etcd for a multi-replica cluster. Run the open-source gateway in your infrastructure, or connect it to **[AISIX Cloud](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=cloud)** for centralized management with team governance, budgets, audit, and a dashboard. > **AISIX AI Gateway (this repo)** is the open-source product. It runs without a control > plane using declarative configuration or etcd. When connected to > **[AISIX Cloud](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=cloud)**, > the same gateway serves as the data plane. AISIX Cloud adds a commercial control plane, > either hosted by API7 (**Hybrid Cloud**) or hosted by you in your infrastructure > (**On-Premises**). In both options, the gateway runs in your environment and calls > providers directly; live AI traffic does not pass through the control plane or API7. > The proxy API is identical throughout. > **[Talk to us about AISIX Cloud →](https://api7.ai/contact?utm_source=github&utm_medium=readme&utm_campaign=cloud)** ## ⚡ Quickstart One container. No control plane, no database, no configuration store — the gateway reads every dynamic resource from one declarative `resources.yaml`. ```yaml # config.yaml resources_file: /etc/aisix/resources.yaml proxy: addr: "0.0.0.0:3000" admin: enabled: false # a declarative gateway needs no admin listener observability: metrics: prometheus: enabled: true addr: "0.0.0.0:9090" ``` ```yaml # resources.yaml _format_version: "1" provider_keys: - display_name: openai-main provider: openai api_key: ${OPENAI_API_KEY} # interpolated from the environment models: - display_name: my-model provider: openai model_name: gpt-4o-mini provider_key: openai-main api_keys: - display_name: local-dev key_env: CALLER_API_KEY # hashed at load; the plaintext is never stored allowed_models: ["my-model"] ``` ```bash export OPENAI_API_KEY="YOUR_PROVIDER_KEY" export CALLER_API_KEY="YOUR_CALLER_KEY" docker run -d --name aisix \ --platform linux/amd64 \ -v "$(pwd)/config.yaml:/etc/aisix/config.yaml:ro" \ -v "$(pwd)/resources.yaml:/etc/aisix/resources.yaml:ro" \ -e OPENAI_API_KEY -e CALLER_API_KEY \ -p 3000:3000 -p 127.0.0.1:9090:9090 \ ghcr.io/api7/aisix:latest # proxy → :3000, metrics + status → :9090 # ^ the metrics/status listener is unauthenticated; # keep it on loopback or a private network ``` Then call the gateway exactly like OpenAI: ```bash curl http://localhost:3000/v1/chat/completions \ -H "Authorization: Bearer $CALLER_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"my-model","messages":[{"role":"user","content":"hello"}]}' ``` Edit `resources.yaml` and send `SIGHUP` (`docker kill -s HUP aisix`) to apply changes with no restart — an invalid file is rejected whole and the last good configuration keeps serving. Check a file before booting with `aisix validate --resources resources.yaml`. Full walkthrough: the [Gateway Quickstart](https://docs.api7.ai/ai-gateway/getting-started/gateway-quickstart) · every field: the [resources file reference](https://docs.api7.ai/ai-gateway/reference/resources-file). For a multi-replica cluster, point the gateway at etcd instead — `resources_file` and `etcd` are mutually exclusive. ## ✨ Why AISIX - **One API, every model.** Speak the OpenAI *or* Anthropic wire format in; the gateway translates to whichever provider each model points at. Point an OpenAI or Claude SDK at one `base_url` and switch models without changing code. - **A real gateway, in Rust.** Single static binary, low cold-start, lock-free config reads on the hot path, native streaming. - **Open source, free forever.** Apache-2.0 licensed and built to run in your infrastructure. Choose AISIX Cloud when you want centralized management through a control plane and dashboard. - **Production controls built in.** Routing & failover, rate limits, guardrails, caching, and observability ship in the box. (Budgets and spend caps are an AISIX Cloud feature — the gateway enforces the control plane's decisions.) ## 🧩 Features — available today Covered by 183 end-to-end scenario files (496 cases) that run against real gateway processes. - **OpenAI-compatible proxy** (`:3000`) — `chat/completions`, `completions`, `responses`, `embeddings`, `rerank`, `images/{generations,edits}`, `audio/{speech,transcriptions,translations}`, `videos` (submit → poll → fetch), `files`, `batches`, `fine_tuning/jobs`, `realtime`, `GET /v1/models`, plus a root-level `/passthrough/:provider/*` escape hatch. Native SSE streaming, tool/function calling, JSON mode, vision/multimodal input, and reasoning-content support. - **Anthropic Messages API** — `POST /v1/messages` as a first-class route, working against **any** configured upstream: requests and responses (including streaming) are translated both ways when a model points at a non-Anthropic provider. - **Routing & failover** — virtual/routing models with six strategies: `round_robin` (smooth weighted round-robin), `consistent_hash` (session affinity keyed by header / cookie / API key / client IP), `failover`, plus metric-based `least_cost`, `least_latency`, and `least_busy`. Per-target `priority` tiers (active/backup pools), retry budgets, cooldowns, tag-conditional targets, and per-attempt timeouts. - **Ensemble models** — fan one request out to a panel of models concurrently, then have a judge model synthesize a single answer, with a minimum-successful-responses threshold. - **Semantic routing** — one virtual model that dispatches by the *meaning* of each request: it embeds the prompt, scores it against per-route example utterances, and routes to the best match (or a default). See the [semantic routing docs](https://docs.api7.ai/ai-gateway/routing/semantic-routing). - **Rate limiting & concurrency** — RPS/RPM/RPH/RPD + TPM/TPD + concurrency caps, AND-combined across caller keys, models, and policy scopes (`api_key` / `model` / `team` / `member` / `team_member`). Counters are per-process by default, or shared across replicas with the Redis backend. - **Guardrails** — content-policy enforcement on input and output, in-process or through a provider: keyword/regex, built-in PII detection and redaction, Presidio, Lakera, OpenAI Moderation, AWS Bedrock Guardrails, Azure AI Content Safety (Prompt Shield + text moderation), and two Alibaba Cloud services. A block returns `422 content_filter`; monitor mode records what would have happened without blocking. - **Caching** — exact-match response cache with per-policy TTL and model/key scope matchers; memory and Redis backends; cost-saved telemetry on every hit. Separately, **automatic prompt caching** can be enabled per direct Anthropic model to inject cache breakpoints, so callers get provider-side prompt discounts without changing their requests. - **MCP gateway** — front registered upstream MCP servers at `/mcp` with gateway-held credentials, per-server tool namespaces, and per-caller access. It serves every Streamable HTTP revision from `2025-03-26` through stateless `2026-07-28` without downstream sessions. Upstreams use `initialize` by default or `server/discover` with `protocol_version: "2026-07-28"`. CI runs the official MCP suite's applicable tools-only protocol scenarios. Also exposes a REST API as MCP tools from its OpenAPI description. - **A2A agent gateway** — front A2A (Agent-to-Agent) agents at `/a2a/:agent`, serving each agent's card with URLs rewritten to the gateway, over JSON-RPC 2.0. - **Inbound authentication** — caller API keys (SHA-256 hashed, model allowlists, expiry, rotation), or OIDC/JWT bearer tokens validated against registered providers (Entra ID, Okta, Google Workspace, or any OIDC issuer) with JWKS caching. - **Observability** — Prometheus `/metrics`, structured per-request access logs, usage events, OTLP/GenAI span export (Langfuse, Honeycomb, Grafana Cloud, or any OTLP receiver), plus dedicated Datadog and Aliyun SLS log exporters and object-storage (S3/GCS/Azure Blob) telemetry. - **Declarative configuration** — one `resources.yaml` carries all ten resource collections (provider keys, models, caller keys, guardrails, MCP servers, A2A agents, cache policies, observability exporters, rate-limit policies, OIDC providers), validated against the same JSON Schemas the gateway uses at runtime. `aisix validate` checks a file offline; `SIGHUP` reloads it atomically. - **Operational endpoints** — `/livez` and `/readyz` on the proxy listener; `/status/config`, `/status/ready`, `/status/models`, and Prometheus `/metrics` on a dedicated metrics listener (`:9090`). The admin listener (`:3001`) additionally serves a **read-only** resource surface, OpenAPI 3 with a Scalar UI, and a playground. Resources are managed declaratively — through the `resources_file` (reloaded on SIGHUP) or direct etcd writes — not through the admin listener; its former write endpoints were removed. ## 🔌 Supported providers AISIX dispatches through **five native adapter families** — distinct wire-protocol bridges, not one generic relabel. Whatever the upstream protocol, the client-facing API stays OpenAI-shaped. | Adapter family | Reaches | Wire shape · auth | |---|---|---| | `openai` | OpenAI **+ any OpenAI-compatible vendor** — DeepSeek, Groq, Mistral, Together, Fireworks, Perplexity, vLLM, Ollama, or self-hosted OpenAI-compatible endpoints | OpenAI chat completions · Bearer | | `anthropic` | Anthropic Claude | Anthropic Messages · `x-api-key` | | `bedrock` | AWS Bedrock — Anthropic, Meta Llama, Mistral, Cohere, Amazon Titan/Nova, AI21 | Bedrock Converse + `/invoke` · SigV4 | | `vertex` | Google Vertex AI (Gemini) | Vertex `:generateContent` · OAuth2 | | `azure-openai` | Azure OpenAI | Azure deployments · api-key / Entra ID | Plus specialized handling for vendor quirks (e.g. DeepSeek reasoning content) and dedicated **rerank / embeddings** vendors (Cohere, Jina). Details in [adapter protocol families](https://docs.api7.ai/ai-gateway/providers/adapters). ## ☁️ Open source vs AISIX Cloud Same gateway binary, same proxy API — in every form the gateway runs in your environment. **AISIX Cloud** adds a commercial control plane, either hosted by API7 (**Hybrid Cloud**) or hosted in your infrastructure (**On-Premises**).

AISIX Cloud overview — requests, latency p50/p99, error rate and cost today, with a 7-day request-and-cost trend and data-plane health

_{Overview — traffic, latency, error rate & spend at a glance}

AISIX Cloud models — alias an upstream LLM per provider (OpenAI, Anthropic, AWS Bedrock, DeepSeek) with model IDs and per-model rate limits

AISIX Cloud models — alias an upstream LLM per provider (OpenAI, Anthropic, AWS Bedrock, DeepSeek) with model IDs and per-model rate limits

_{Models — one alias per upstream: OpenAI, Anthropic, Bedrock, DeepSeek…}

AISIX Cloud guardrails — pre-input and post-output content policies (keyword blocklist, Azure Content Safety, AWS Bedrock) that block on violation

AISIX Cloud guardrails — pre-input and post-output content policies (keyword blocklist, Azure Content Safety, AWS Bedrock) that block on violation

_{Guardrails — pre-input & post-output policies, block on violation}

AISIX Cloud playground — pick a model, set system and user prompts, run, and read the response with live token and cost metering

_{Playground — test any model with live token & cost metering}

AISIX Cloud observability exporters — fan out chat-completion telemetry to OTLP, Datadog and object storage, with per-target delivery health

AISIX Cloud observability exporters — fan out chat-completion telemetry to OTLP, Datadog and object storage, with per-target delivery health

_{Observability — fan out traces & logs to OTLP, Datadog, object storage}

AISIX Cloud budgets — organization and per-environment spend caps with progress bars, hard-stop versus warn-only, including an over-budget policy

AISIX Cloud budgets — organization and per-environment spend caps with progress bars, hard-stop versus warn-only, including an over-budget policy

_{Budgets — hard-stop spend caps with warn-only tiers}

The AISIX Cloud dashboard — overview metrics, multi-provider models, guardrails, budgets (with hard-stop spend caps), and observability exporters, across all your gateways.

▶ Try the live dashboard demo — aisix-demo.api7.ai

| | Open-source gateway (this repo) | [AISIX Cloud](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=cloud) (Hybrid Cloud or On-Premises) | |---|---|---| | Price | Free · Apache-2.0 · forever | Commercial — [talk to us](https://api7.ai/contact?utm_source=github&utm_medium=readme&utm_campaign=pricing) | | Configuration | Declarative `resources.yaml`, or etcd for a cluster | Dashboard + Cloud Admin API, multi-environment | | Tenancy | Single instance / namespace | Org → Team → Member → Environment | | Provider keys | In the resources file as `${VAR}` env references, or in etcd | Envelope-encrypted at rest, write-only, in-place rotation | | Inbound auth | Caller keys (SHA-256 hashed, model allowlists, expiry), or OIDC/JWT bearers | Same, plus masked reveal, key ownership, and PATs | | Budgets | — (rate and token limits only) | Per key / provider / env / org / team, hard-stop & alerts | | RBAC | Admin key = read-only resource surface | Org roles (owner / admin / member), invites | | Audit log | — | Full org-scoped audit with diff viewer | | Usage & cost | Export logs, metrics, and usage events yourself | Managed usage views, model pricing catalog, spend reporting | | Surface | Status endpoints, OpenAPI read surface, playground | Full dashboard + per-environment playground | → **Want the AISIX Cloud control plane, governance, budgets, and dashboard?** **[Talk to API7](https://api7.ai/contact?utm_source=github&utm_medium=readme&utm_campaign=cloud)** about Hybrid Cloud or On-Premises, or **[book a demo](https://api7.ai/contact?utm_source=github&utm_medium=readme&utm_campaign=demo)**. ## 🏗️ Architecture A single Cargo workspace; the `aisix-server` crate builds one binary named `aisix` that wires the crates together. ```text crates/ ├── aisix-core Config, snapshot, resource model, resources.yaml source, errors ├── aisix-etcd Config provider + watch supervisor ├── aisix-gateway Hub & bridge, SSE parser, provider trait ├── aisix-proxy /v1/*, /mcp, /a2a handlers, routing, middleware ├── aisix-admin Read-only resource surface + playground + OpenAPI ├── aisix-provider-* openai · anthropic · azure-openai · bedrock · vertex ├── aisix-mcp MCP gateway — server registry, tool ACL, transports ├── aisix-a2a A2A agent gateway — agent cards, JSON-RPC bridge ├── aisix-ratelimit fixed-window + token accounting + concurrency (local | redis) ├── aisix-cache memory + redis backends ├── aisix-redis shared Redis connection for cache + rate limits ├── aisix-guardrails pre/post content-policy hooks ├── aisix-obs tracing, metrics, access log, exporters └── aisix-server the `aisix` binary — bootstrap + CLI ``` ## 🗺️ Roadmap Highlights on the [roadmap](https://github.com/api7/aisix/blob/HEAD/ROADMAP.md); tracked live in [issues](https://github.com/api7/aisix/issues): - Semantic (embedding-similarity) response caching - More observability sinks — Langsmith, Helicone, Slack alerts - Prompt templates managed as gateway resources - Llama-Guard as a guardrail provider Shipped since this list was last written: the MCP gateway, the A2A agent gateway, OIDC/JWT inbound auth, Redis-backed distributed rate limiting, and the Lakera, Presidio, PII, and OpenAI Moderation guardrails — see **Features** above. ## 🛠️ Development Prerequisites: the Rust toolchain pinned in `rust-toolchain.toml`. Docker is only needed for the tests that exercise etcd, Redis, or provider emulators. ```bash cargo check --workspace cargo fmt --check cargo clippy --workspace -- -D warnings cargo test --workspace # Coverage (matches the CI gate) cargo llvm-cov --workspace --lcov --output-path lcov.info # Run locally against a resources.yaml (no etcd needed). Copy the Quickstart's two files # and change resources_file to the local path, e.g. resources_file: ./resources.yaml cargo run -p aisix-server --bin aisix -- --config config.local.yaml # Check a resources file without starting a listener cargo run -p aisix-server --bin aisix -- validate --resources resources.yaml ``` ## 💬 Community - **Discord** — [discord.gg/dUmRZ7Rvf](https://discord.gg/dUmRZ7Rvf) - **Issues & discussions** — [github.com/api7/aisix/issues](https://github.com/api7/aisix/issues) - **Contributing** — [CONTRIBUTING.md](https://github.com/api7/aisix/blob/HEAD/CONTRIBUTING.md) - **Website** — [api7.ai/ai-gateway](https://api7.ai/ai-gateway?utm_source=github&utm_medium=readme) If AISIX is useful to you, a ⭐ helps other engineers find it. ## 📄 License [Apache 2.0](https://github.com/api7/aisix/blob/HEAD/LICENSE).