Zero Trust Agent Identity Pipeline
Zero-trust AI agent identity architecture with JWT validation, scoped OBO token exchange, SPIFFE/SVID workload identity, and MCP tool authorization.
MCP security gateway architecture that authenticates tool calls, routes execution into isolated sandboxes, sanitizes responses, and returns clean results to the AI agent.
Agent { # AI Agent
n1: circle label:"Start"
n2: rectangle label:"Request tool invocation"
n3: rectangle label:"Receive clean response"
n4: circle label:"Done"
n1.handle(right) -> n2.handle(left)
n2.handle(bottom) -> MCPGateway.n5.handle(top) [label="Tool call + OBO token"]
n3.handle(right) -> n4.handle(left)
}
MCPGateway { # MCP Security Gateway
n5: rectangle label:"Authenticate + check registry"
n6: rectangle label:"Route to sandbox"
n7: rectangle label:"Receive sandbox result"
n8: rectangle label:"Forward clean response"
n5.handle(right) -> n6.handle(left)
n6.handle(bottom) -> ToolSandbox.n9.handle(top) [label="Sandbox request"]
n7.handle(right) -> n8.handle(left)
n8.handle(top) -> Agent.n3.handle(bottom) [label="Sanitized response"]
}
ToolSandbox { # Tool Sandbox
n9: rectangle label:"Execute in isolated container"
n10: rectangle label:"Validate response"
n11: rectangle label:"Strip injection payloads"
n12: rectangle label:"Return clean result"
n9.handle(right) -> n10.handle(left)
n10.handle(right) -> n11.handle(left)
n11.handle(right) -> n12.handle(left)
n12.handle(top) -> MCPGateway.n7.handle(bottom) [label="Clean result"]
}
Zero-trust AI agent identity architecture with JWT validation, scoped OBO token exchange, SPIFFE/SVID workload identity, and MCP tool authorization.
A single-agent AI architecture where one agent handles everything: parsing requests, reasoning, calling tools via MCP, and generating responses. This is the default architecture for prototypes and simple automations—easy to debug but hits context-window limits quickly and is hard to parallelize. Ideal for MVPs and solo builders shipping fast.
The simplest AI-native architecture — a single agent that receives user input, reasons, plans, decides on tool calls, processes results, and generates responses. Direct MCP connection over stdio or HTTP. Best for MVPs and when low latency matters.
Claw Code harness architecture diagram showing the user loop, Python orchestration layer, Rust runtime, and external systems such as the LLM provider, file system, and MCP server.
Least-privilege AI agent architecture with policy-engine evaluation, just-in-time access, short-lived credentials, and action-scoped grants before tool execution.
Human-in-the-loop approval architecture that scores agent actions by risk, routes high-risk requests for review, and writes immutable audit records.