Integrations
Connect SmartGate with the tools you already use — browse integrations for observability, authentication, and AI infrastructure.
Verified Connectors & Tools
Role guides
Connect OpenClaw to SmartGate over MCP: Config and Guardrails
OpenClaw MCP setup in four steps: point OpenClaw at a Streamable HTTP MCP endpoint, send the Bearer plus platform headers, then cap tool traffic with per-plan rate limits, a hard budget guard.
AI Agent Architecture: LangGraph vs CrewAI vs a Gateway
An AI agent architecture is drawn as four layers and decided as a framework choice. The twelve shipped symbols here cover what neither LangGraph nor CrewAI decides: registration.
Optimize AI Agent Execution Cost: Meter, Attribute, Prove
Optimising AI agent execution cost starts with attribution, not model choice: record usage at the gateway, infer tokens when a tool omits them, count with the right tokeniser.
Build a Low-Cost AI Backend Architecture: Count, Cache, Meter
A low-cost AI backend is four cost decisions, not a cheaper model: price each call, cache and batch what repeats, route on cost per resolved task, and self-host only past a computed break-even.
AI Financial Analysis for Agents: From Audit Log to Report
AI financial analysis with agents is an accounting problem before it is a model problem. Seven shipped functions price a call against a team, a window and a budget.
AI Automation for SaaS Operations: Queues, Webhooks, Billing
AI workflow automation in a SaaS product is three primitives, not a canvas: a durable email queue, a webhook intake that verifies before it deduplicates.
Concurrency Control in AI Backend Systems: Limits, Queues, Pools
Concurrency control in an AI backend has five layers: a plan catalog that decides the numbers, a two-level MCP limiter per key and per team, an edge sliding window for bursts.
API Documentation Best Practices for AI Tools: Generators, Specs
Twelve API documentation best practices for AI tools, each with code: publish a machine-readable spec, give agents annotations, test the docs against the code, enforce a frontmatter contract.
Prompt Security for AI Applications: Policy, Keys, Audit
Prompt security is five layers, not one filter: a schema-validated policy per team, a clamp that only tightens, a key check on every request, masking before the log is written.
Token Optimization Techniques for AI Apps: Caps and Cost Control
Token optimization for AI apps: measure usage, shape prompts, cache repeats, route by price, cap output. Eight techniques with the gateway code behind them.
AI Gateway vs API Gateway: Where Each Responsibility Sits
An AI gateway and an API gateway share routing, auth and request rate limits; they part at per-key token quota, cost accounting, the audit row per task and tool proxying.