MCP server AISIX AI Gateway
Коммит 13 нояб. 2026 г.Предоставляет единый OpenAI-совместимый API для маршрутизации, управления, защиты и мониторинга трафика между несколькими провайдерами LLM и MCP server.
Также известен как api7/aisix, aisix
- Звёзды
- 219
- Инструменты
- —
- Загрузки, 30 дней
- —
- Последняя версия
- 1.3.0
- Последний коммит
- 13 нояб. 2026 г.
- Лицензия
- Apache-2.0
Что такое AISIX AI Gateway MCP?
AISIX AI Gateway — это MCP server. Предоставляет единый OpenAI-совместимый API для маршрутизации, управления, защиты и мониторинга трафика между несколькими провайдерами LLM и MCP server.
Сводка сгенерирована из README проекта
О AISIX AI Gateway MCP server
AISIX OSS — это написанный на Rust AI gateway, разработанный для платформенных команд, чтобы управлять трафиком LLM и AI agent через единую точку управления. Он предоставляет OpenAI-совместимый API, который служит унифицированным интерфейсом для различных провайдеров, включая OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI и DeepSeek. Развертывая этот единый статический бинарный файл в собственной инфраструктуре, вы можете маршрутизировать, защищать и отслеживать запросы, не пропуская рабочий трафик через сторонние панели управления.
Шлюз берет на себя сложные операционные задачи, такие как семантическая маршрутизация, выполнение ансамблей моделей и автоматическое переключение при сбоях с использованием таких стратегий, как round robin или выбор модели с наименьшей задержкой. Он включает встроенные механизмы защиты для обнаружения PII и соблюдения политик контента, а также возможности кэширования с использованием memory или Redis бэкендов. Пользователи управляют системой через декларативный файл resources.yaml или кластер etcd, что позволяет выполнять горячую перезагрузку конфигурации через SIGHUP без перезапуска сервиса.
Что вы можете с ним делать
- 1Единый доступ к моделямРазработчик может переключаться между различными провайдерами LLM, просто изменив название модели в существующем коде с использованием OpenAI SDK.
- 2Безопасное управление MCP serverВы можете предоставлять доступ к нескольким MCP server через шлюз, сохраняя строгий контроль над пространствами имен инструментов и учетными данными вызывающих сторон.
- 3Интеллектуальная маршрутизация запросовAI клиент может автоматически отправлять промпты наиболее подходящей модели на основе фактического смысла пользовательского ввода.
- 4Контроль безопасности контентаПлатформенные инженеры могут внедрить автоматическое удаление конфиденциальной информации и блокировку запрещенного контента, используя различные инструменты модерации.
Взято из README проекта. Каждый вариант использования проверен на соответствие цитате из него.
Как установить AISIX AI Gateway MCP
Форматы проверены 10 ноя 2026Установка AISIX AI Gateway MCP в Claude Code
$ claude mcp add aisix -- docker run -i --rm ghcr.io/api7/aisix:1.3.0Установка AISIX AI Gateway MCP в Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"aisix": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/api7/aisix:1.3.0"
]
}
}
}Установка AISIX AI Gateway MCP в VS Code
.vscode/mcp.json
{
"servers": {
"aisix": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/api7/aisix:1.3.0"
]
}
}
}Установка AISIX AI Gateway MCP в Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"aisix": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/api7/aisix:1.3.0"
]
}
}
}Установка AISIX AI Gateway MCP в Codex
~/.codex/config.toml
[mcp_servers.aisix] command = "docker" args = ["run", "-i", "--rm", "ghcr.io/api7/aisix:1.3.0"]
Установка AISIX AI Gateway MCP в Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"aisix": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/api7/aisix:1.3.0"
]
}
}
}Конфигурация
CALLER_API_KEYOPENAI_API_KEY
| Название | Описание | Тип |
|---|---|---|
| CALLER_API_KEY | — | |
| OPENAI_API_KEY | — |
Автоматические проверки
Запущено 12 нояб. 2026 г.Полный отчёт →Еще не проверено. Для сервера требуется оценка 80, отсутствие серьезных проблем и достаточно данных для нашей проверки. Как работают проверки
- Связанный и доступный исходный репозиторийПройдено
- Open source лицензия (OSI)Пройдено
- Коммит или релиз за последний годПройдено
- Имя пакета не похоже на популярный пакетНе проверялось
- Удаленная конечная точка использует HTTPSНе проверялось
- Деструктивные инструменты помеченыНе проверялось
- Нет скрытых инструкций для моделиПройдено
- Нет критических уязвимостей в пакете и зависимостяхНе проверялось
README
Открыть на GitHubAISIX OSS
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.
Start free · Documentation · Quickstart · AISIX Enterprise and AISIX Cloud · Roadmap
AISIX OSS is the open-source product built around the Rust-native AISIX gateway. The gateway 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
gateway in your infrastructure, or connect it to AISIX Enterprise or
AISIX Cloud
for centralized management with team governance, budgets, audit, and a dashboard.
AISIX OSS (this repo) is the open-source product. It runs without a control plane using declarative configuration or etcd. The same gateway binary serves as the data plane in the commercial products: customers host the control plane with AISIX Enterprise, while API7 hosts it with AISIX Cloud. In all three products, the gateway runs in your environment and calls providers directly; live AI traffic does not pass through either control plane. The proxy API is identical throughout. Talk to us about AISIX Enterprise or AISIX Cloud →
⚡ Quickstart
One container. No control plane, no database, no configuration store — the gateway reads
every dynamic resource from one declarative resources.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"
# resources.yaml
_format_version: "1"
provider_keys:
- display_name: openai-main
provider: openai
api_key: ${OPENAI_API_KEY} # interpolated from the environment
models:
- display_name: my-model
provider: openai
model_name: gpt-4o-mini
provider_key: openai-main
api_keys:
- display_name: local-dev
key_env: CALLER_API_KEY # hashed at load; the plaintext is never stored
allowed_models: ["my-model"]
export OPENAI_API_KEY="YOUR_PROVIDER_KEY"
export CALLER_API_KEY="YOUR_CALLER_KEY"
docker run -d --name aisix \
-v "$(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:
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 ·
every field: the resources file reference.
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_urland 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 Enterprise or 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 AISIX Enterprise and AISIX Cloud features — 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/messagesas 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-basedleast_cost,least_latency, andleast_busy. Per-targetprioritytiers (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.
- 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
/mcpwith gateway-held credentials, per-server tool namespaces, and per-caller access. It serves every Streamable HTTP revision from2025-03-26through stateless2026-07-28without downstream sessions. Upstreams useinitializeby default orserver/discoverwithprotocol_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.yamlcarries 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 validatechecks a file offline;SIGHUPreloads it atomically. - Operational endpoints —
/livezand/readyzon the proxy listener;/status/config,/status/ready,/status/models, and Prometheus/metricson 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 theresources_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.
☁️ Choose an AISIX Product
Same gateway binary, same proxy API — in every form the gateway runs in your environment. AISIX Enterprise adds a customer-hosted commercial control plane. AISIX Cloud adds an API7-hosted commercial control plane.
| AISIX OSS (this repo) | AISIX Enterprise | AISIX Cloud | |
|---|---|---|---|
| License | Apache-2.0 | Commercial | Commercial |
| Control plane | None | Customer-hosted | API7-hosted |
| Configuration | Declarative resources.yaml, or etcd for a cluster |
Dashboard + AISIX Cloud Admin API | Dashboard + AISIX Cloud Admin API |
| Tenancy | Single instance / namespace | Organization-scoped environments, teams, and members | Organization-scoped environments, teams, and members |
| Provider keys | ${VAR} references in resources.yaml; plaintext credentials in etcd |
Encrypted at rest; operator-triggered in-place rotation | Encrypted at rest; operator-triggered in-place rotation |
| Budgets | — (rate and token limits only) | Per key, provider, environment, organization, and team | Per key, provider, environment, organization, and team |
| RBAC and audit | Local admin key; no organization layer | Organization roles, invitations, and audit history | Organization roles, invitations, and audit history |
| Operations | You operate the gateway | You operate the control plane and gateways | API7 operates the control plane; you operate gateways |
→ Want centralized governance, budgets, and a dashboard? Talk to API7 about AISIX Enterprise or AISIX Cloud, or book a demo.
🏗️ Architecture
A single Cargo workspace; the aisix-server crate builds one binary named aisix that
wires the crates together.
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; tracked live in 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.
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
- Issues & discussions — github.com/api7/aisix/issues
- Contributing — CONTRIBUTING.md
- Website — api7.ai/ai-gateway
If AISIX is useful to you, a ⭐ helps other engineers find it.
📄 License
Вопросы о AISIX AI Gateway MCP
Как добавить AISIX AI Gateway MCP в Claude Code?
Выполните claude mcp add aisix -- docker run -i --rm ghcr.io/api7/aisix:1.3.0 в терминале. Добавьте --scope user, чтобы сервер был доступен во всех проектах.
Как добавить AISIX AI Gateway MCP в Cursor?
Откройте ~/.cursor/mcp.json и добавьте сервер в mcpServers, используя конфигурацию Cursor из раздела установки выше.
Как применить изменения конфигурации без перезапуска шлюза?
Вы можете атомарно перезагрузить конфигурацию, отправив сигнал SIGHUP процессу после редактирования файла resources.yaml.
Поддерживает ли AISIX MCP server?
Да, он работает как MCP gateway, который предоставляет доступ к зарегистрированным вышестоящим MCP server с разделением пространств имен инструментов для каждого сервера и разграничением прав доступа для каждого вызывающего пользователя.
Могу ли я использовать AISIX с моделями Anthropic через формат OpenAI?
Да, шлюз транслирует форматы передачи данных OpenAI или Anthropic, что позволяет вам направлять OpenAI SDK на шлюз для доступа к различным провайдерам.
Какие механизмы безопасности и защиты (guardrails) включены?
В систему включены инструменты соблюдения политик контента, обнаружение и удаление PII (персональных данных), а также интеграция с такими сервисами, как OpenAI Moderation и AWS Bedrock Guardrails.