Integrations and APIs
Integration between services and APIs in practice: HTTP, webhooks, limits, authorization, retros and stable operation of external dependencies.
How to get AI to connect the API correctly the first time
AI often connects APIs “at will”: without error processing, with keys in the code and without considering limits – and everything breaks down in the market
MCP in AI Development: Secure Tool Connection
Practical analysis of how to connect MCP tools to AI agents without leaks, unnecessary rights and chaos in access: roles, proxy, audit and working checklist.
AI Integration Contract Tests: How to Stabilize APIs
Step-by-step analysis of contract tests for AI integrations: how to fix API expectations, catch regressions before production and reduce the cost of errors.
Idempotence of AI integrations: how to remove duplicates and losses
A practical guide to idempotence in AI integrations: how to eliminate duplicate operations, protect payments and stabilize piplins in retrogrades.
What is webhook in simple words and how not to lose events
A practical guide to working with webhook for developers: from basic understanding to reliable production architecture. The article explains what webhook is, why events can get lost, and how to properly build processing to avoid duplicates and errors.
Rate Limit and Retry: A Basic Scheme for Reliable Integrations
A practical explanation of how rate limit and retry work in API integrations. The article deals with why servers limit the number of requests, how to properly handle errors and repeated attempts, what is exponential backoff and jitter, and how to build a basic query architecture without overloading the API.