Gateway
An intermediary layer positioned between clients and backend services that handles cross-cutting concerns such as request routing, authentication, rate limiting and quota management.
Core Facts
An AI gateway centrally handles responsibilities such as unified entry point and routing, access control and identity governance, compliance and audit trail, and cost and usage observability.
The Gateway in Claude Code acts as an API gateway and serves as the unified entry point for users to configure and manage different AI model interfaces.
Timeline (last 90 days)
MCP makes tool integration simple, but integration is only the starting point; the real security boundary lies in the Gateway's per-request checks, not in the moment of "successful connection".
Doordash's practice shows that an AI agent being able to connect to an MCP server does not mean it can call all the tools on that server; the Gateway performs permission checks on each request.
Concentrating permission decisions in the Gateway brings three benefits: changing or revoking permissions requires changing only one place; the Dev agent does not need to stuff security rules into the prompt; and tool owners do not need to rewrite authorization logic.
The caller's identity travels through the entire chain with the request—from routing and forwarding and usage logging all the way to the final executed action—thereby enabling traceability.
Some workflows run under a team identity with a stable permission boundary, whereas an individual's separate operations require explicit authorization by that person.
The Gateway's policy engine makes permission decisions by combining multiple dimensions: which agent it is, which user it represents, which tool is being called, and what environment the request is in.
On each tool call, the Gateway must answer two questions: Authentication addresses "who is calling", and Authorization addresses "what the caller is allowed to do".
The gateway is part of the orchestration layer, but it is not the security boundary itself; treating the gateway as the only line of defense is equivalent to assuming that all calls will pass through the gateway.
Many Agent frameworks design the gateway as a security hub responsible for authentication, auditing, and rate limiting, but in scenarios involving sub-agents, mixed use of multiple frameworks, and self-hosted runtimes, the gateway's coverage becomes fragile.
Whether runtime security can protect Agents that can bypass the gateway depends on its definition: if it is merely policy code inside the gateway, it cannot protect them; if it is a defense-in-depth system covering credential management, network isolation, and token issuance, it can provide a fallback.
7 more timeline events
All Facts (20)
An AI gateway centrally handles responsibilities such as unified entry point and routing, access control and identity governance, compliance and audit trail, and cost and usage observability.
75%VerifiedThe Gateway in Claude Code acts as an API gateway and serves as the unified entry point for users to configure and manage different AI model interfaces.
65%Unverified芋道Cloud模块间通过Feign进行服务调用，结合Gateway实现统一网关路由
90%UnverifiedOpenClaw的Dashboard只是前端展示层，真正的业务逻辑全部由Gateway驱动
90%UnverifiedOpenClaw的Gateway是一个本地运行的RPC服务器，负责将来自飞书、钉钉等渠道的消息请求统一接收，再调度给底层的AI模型和工具插件处理
85%Unverifiedopenclaw gateway 命令用于前台启动OpenClaw的Gateway网关服务
55%UnverifiedMCP makes tool integration simple, but integration is only the starting point; the real security boundary lies in the Gateway's per-request checks, not in the moment of "successful connection".
50%UnverifiedDoordash's practice shows that an AI agent being able to connect to an MCP server does not mean it can call all the tools on that server; the Gateway performs permission checks on each request.
50%UnverifiedOn each tool call, the Gateway must answer two questions: Authentication addresses "who is calling", and Authorization addresses "what the caller is allowed to do".
50%UnverifiedThe Gateway's policy engine makes permission decisions by combining multiple dimensions: which agent it is, which user it represents, which tool is being called, and what environment the request is in.
50%UnverifiedSome workflows run under a team identity with a stable permission boundary, whereas an individual's separate operations require explicit authorization by that person.
50%UnverifiedThe caller's identity travels through the entire chain with the request—from routing and forwarding and usage logging all the way to the final executed action—thereby enabling traceability.
50%UnverifiedConcentrating permission decisions in the Gateway brings three benefits: changing or revoking permissions requires changing only one place; the Dev agent does not need to stuff security rules into the prompt; and tool owners do not need to rewrite authorization logic.
50%UnverifiedThe gateway is part of the orchestration layer, but it is not the security boundary itself; treating the gateway as the only line of defense is equivalent to assuming that all calls will pass through the gateway.
50%UnverifiedWhether runtime security can protect Agents that can bypass the gateway depends on its definition: if it is merely policy code inside the gateway, it cannot protect them; if it is a defense-in-depth system covering credential management, network isolation, and token issuance, it can provide a fallback.
50%UnverifiedMany Agent frameworks design the gateway as a security hub responsible for authentication, auditing, and rate limiting, but in scenarios involving sub-agents, mixed use of multiple frameworks, and self-hosted runtimes, the gateway's coverage becomes fragile.
50%UnverifiedGateway retains the original string and JSON request formats, rejects file-type inputs, and TypeSafe AI adopts the same strategy.
50%UnverifiedRead operations by Agents can be left open, but every write path must be bound to a real user's permission verification.
50%UnverifiedGovernance of agents must enforce fine-grained policy interception on every tool call and every data access.
50%UnverifiedGateway-based governance transforms security, compliance, and observability from post-hoc remediation into real-time interception.
50%