Nango, connectors, Slack/Gmail/Drive ingestion, webhooks, and MCP connectors. 8 articles, written by the engineers building AI App Lab.
AI Google Drive integration: RAG-powered semantic search, document ingestion pipeline, incremental sync with Drive Changes API, vector embeddings, ACL preservation, and enterprise Drive-as-knowledge-base architecture patterns.
AI Gmail integration: Gmail API for email triage, summarization, draft replies, classification, Google Workspace OAuth, Pub/Sub push notifications, and enterprise AI email agent architecture patterns.
AI webhook data sync: centralized webhook hub, HMAC signature verification, idempotent processing, dead letter queues, exponential backoff retry, fan-out dispatch, and enterprise event-driven AI agent architecture patterns.
AI Slack integration: event subscriptions, slash commands, app mentions, interactive messages, Slack Bolt SDK, agent context, thread summarization, approval workflows, and enterprise Slack AI agent architecture patterns.
AI GitHub knowledge base: AST-based code chunking with tree-sitter, GraphRAG with Neo4j call graphs, hybrid search with BM25 and vector similarity, MCP tools for AI agents, incremental sync, and enterprise codebase intelligence patterns.
AI Jira Linear integration: MCP servers for ticket management, bidirectional sync, issue-driven development, agent sessions, ticket-to-code-to-status flows, Linear API for agentic workflows, and enterprise project management automation patterns.
AI Notion integration: Notion MCP for AI agents, Custom Agents with triggers, Workers for custom code, database sync, RAG from Notion pages, enterprise governance, and workspace-as-knowledge-base architecture patterns.
Nango AI integrations: managed OAuth for 800+ APIs, token refresh automation, TypeScript integration functions, AI-generated integrations, multi-tenant credential isolation, and unified API platform for AI agents and RAG pipelines.