Blog
Thoughts on building integrations for AI agents, shipping multi-tenant OAuth, and growing the Corsair open-source ecosystem.
Building the same Slack, Gmail, GitHub, or CRM integration for every AI agent framework creates unnecessary authentication and maintenance work. Learn how to separate your integration layer from framework-specific adapters so you can build integrations once and reuse them across multiple frameworks.
Read articleWorkflow engines orchestrate business processes, while integration platforms manage the authentication, permissions, and connectivity behind SaaS tools. Learn why combining both can help AI products scale workflows and agents without duplicating integration logic.
Read articleAI integrations rely on layers of open source dependencies that can introduce security, maintenance, licensing, and compatibility risks. Learn how to vet dependencies, monitor vulnerabilities, build a scalable management strategy, and respond when a package becomes outdated or unmaintained.
Read articleProvider API changes can quietly break MCP integrations through renamed fields, changed scopes, altered pagination, or new response formats. Learn how to detect changes early, isolate provider-specific updates, roll out migrations safely, and build resilient MCP servers that keep AI agents working.
Read articleGoogle API deprecations can quietly break AI integrations when endpoints, fields, response formats, or authentication requirements change. Learn how to identify affected integrations, plan migrations, test API changes, and keep AI products reliable across Google API versions.
Read articleLearn how to connect Google Sheets to AI agents using the Google Sheets API, Google's official MCP server, Apps Script, and no-code automation tools. Compare each approach, discover best practices, and choose the right architecture for your AI workflows.
Read articleLearn how to build a scalable AI agent builder with Model Context Protocol (MCP). Explore the architecture, connection management, authentication, tool discovery, observability, and best practices for creating production-ready AI platforms.
Read articleLearn how open source integration layers help B2B AI products securely connect with external systems. Explore connector frameworks, OAuth, secret isolation, MCP support, observability, multi-tenancy, and best practices for building production-ready AI agents.
Read articleLearn why integration platforms are essential for production AI agents. Discover how they simplify authentication, credential management, observability, retries, MCP support, and API integrations while reducing engineering overhead.
Read articleDiscover the essential developer tools for AI agent integrations, including logging, observability, structured tracing, MCP servers, credential management, and best practices for building reliable production AI systems.
Read articleLearn the best practices for building reliable API integrations that withstand API changes through versioning, schema validation, authentication, monitoring, and resilient design.
Read articleLearn what intelligent workflow automation is, how AI agents enhance workflows, and why orchestration platforms are essential for scalable business automation.
Read articleLearn how to evaluate an open source project before adopting it by reviewing licensing, governance, security, documentation, production readiness, and AI workflow compatibility.
Read articleLearn how to set up a Google Drive MCP server for Claude Code using OAuth, connect AI agents securely to Google Drive, troubleshoot common issues, and scale with Corsair.
Read articleLearn why AI agents need an integration layer instead of direct API connections, how reusable connectors and MCP fit together, and what to look for in a production-ready platform.
Read articleAPI keys pile up quietly across config files, CI pipelines, and third party dashboards until one overlooked key exposes more than a single account. This guide covers scoping, rotation, and what changes once AI agents start acting on your users' behalf.
Read articleClosed source integration tools rarely fail loudly. They just put a ceiling on what you can ship, one missing endpoint and one inflexible permission model at a time.
Read articleOAuth setup feels trivial for one integration and turns into an ongoing maintenance job across ten. This post breaks down what manual OAuth really costs a team, why refresh tokens and redirect URIs keep breaking workflows, and what changes when a platform owns that layer instead.
Read articleWiring an AI agent to four tools usually means building four integrations, four auth flows, and four things to maintain. This post looks at how an MCP based layer replaces that with a single connection that holds up as you keep adding tools.
Read articleGmail looks like a simple integration until you hit consent screens, scope reviews, and expiring tokens. This walkthrough covers what it actually takes to connect an AI agent to Gmail and keep it working in production for real users.
Read articleOpen source vs closed source integration tools for AI agents — how the choice affects vendor lock-in, security transparency, long-term cost, and your ability to ship integrations on your own timeline.
Read articleA TypeScript developer's guide to wiring integration layers into both the Claude Agent SDK and OpenAI Agents SDK — how tool definitions, hooks, guardrails, and tenant isolation differ across each framework.
Read articleWhy webhooks alone can't support what AI agents actually need — synchronous access, tenant-aware permissions, and flexible tool execution within a single reasoning step.
Read articleWhy closed source integration platforms are a security risk for AI agents — and how open source TypeScript frameworks with self-hosted options give you the auditability multi-tenant AI products need.
Read articleBest practices for multi-tenant OAuth in AI agents — how to structure credential management, scope permissions per tenant, and avoid the mistakes that turn auth into a security liability.
Read articleHow to connect Google Drive to OpenAI Agents SDK — turn passive cloud storage into an intelligent layer your AI agent can search, organize, and share files through naturally.
Read articleA developer's guide to Claude Agent SDK integrations, how to wire in custom tools like Jira, Slack, and Google Drive without turning each one into a maintenance project.
Read articleSelf-hosted vs managed integration platforms — what AI teams actually need to know about data control, cost, and choosing the right integration platform as a service.
Read articleDiscover how MCP integration helps businesses connect AI agents to external tools securely, reduce engineering complexity, and scale reliable AI automation with ease.
Read articleClassic iPaaS tools like Zapier and MuleSoft were built for fixed, pre-defined workflows not for AI agents that decide in real time which apps to touch and in what order. Here's why that model breaks for agents, and what a typed, callable integration layer looks like instead.
Read articleLearn what Google APIs are, how they work, and how to integrate services like Maps, Gmail, Drive, and Calendar securely into modern applications and AI agents.
Read articleA developer experience deep dive into building AI agent integrations in TypeScript — typed tool calling, OAuth vs API keys, and webhook security done right.
Read articleLearn how MCP servers connect AI agents to GitHub, Slack, Notion, Linear, Stripe, and more, and discover what to look for when choosing an MCP integration layer.
Read articleLearn how to securely connect AI agents with Google Drive, Calendar, and Sheets using OAuth, MCP, permission gates, and multi-tenant integrations.
Read articleCompare open-source and closed-source integration platforms for AI agents. Learn how vendor lock-in, pricing, security, and extensibility affect long-term product strategy.
Read articleAnthropic launched Claude Fable 5, a Mythos-class model made safe for general use, alongside Claude Mythos 5 for trusted partners — with new safeguards, pricing, and availability details.
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