Mcp Plumbing
MCP, Connectors & Plumbing brings this topic into one place so the full arc is easy to follow. Start anywhere, or move through the pieces in order to build a cleaner read on mcp plumbing. The Series MCP Explained: What It Is and Why It MattersCustomclankerPlumbing Maintenance: What Breaks and
Mcp Plumbing
Every AI product ships with a marketing page that says "integrates with 1,000+ tools." The number is always large, always round, and always misleading. What it actually means: a Zapier connector exists, or someone wrote an MCP server six months ago, or there's a REST
Mcp Plumbing
This article is not about data engineering. It's not about Spark clusters, Kafka streams, or petabyte-scale ETL. It's about what happens when a solo developer or small team needs to process a few hundred to a few thousand items through an LLM — classify them, extract structured
Mcp Plumbing
Before you promise a client — or yourself — that "the AI can connect to X," check this. The marketing pages say "integrates with 1,000+ tools." The reality is that integration quality exists on a spectrum from production-grade to vaporware, and the number on the marketing page
Mcp Plumbing
Webhooks are the event-driven plumbing underneath most of the internet's automation layer. Service A sends an HTTP POST to a URL you control whenever something happens — a payment completes, a commit lands, a form gets submitted. It's conceptually simple. In practice, the gap between "conceptually
Mcp Plumbing
The hardest part of connecting AI to anything is not the AI. It's not the model, the prompt engineering, the MCP server, the connector ecosystem, or whatever the latest abstraction layer calls itself. It's authentication. The boring, unglamorous, deeply annoying process of proving to one computer
Mcp Plumbing
Three ways to connect AI tools to external services: no-code platforms like Zapier and Make, direct API integration, and MCP servers. Each has a sales pitch. Zapier says you don't need developers. API integration says you don't need abstractions. MCP says you don't need
Mcp Plumbing
You've looked at the MCP server ecosystem. Nothing covers your internal API, or the existing server for your service is broken, or your use case is specific enough that no generic server fits. So you're thinking about building your own. Good — custom MCP servers are sometimes
Mcp Plumbing
There are hundreds of MCP servers available right now. The GitHub topic page for "mcp-server" returns a wall of repositories. Registries like Smithery list hundreds more. The ecosystem looks enormous — until you start actually using them. Then the number that work reliably, handle errors gracefully, and survive a
Mcp Plumbing
Nobody budgets for maintenance. The pitch deck shows the architecture diagram with clean arrows between services. The sprint plan covers building the integrations. The roadmap shows the features those integrations enable. Nowhere in any of these documents is a line item that says "keep this working after we build
Mcp Plumbing
Anthropic's Model Context Protocol — MCP — is an open standard for connecting LLMs to external tools and data sources. It launched in late 2024 and has since become the closest thing the AI tool ecosystem has to a shared plumbing specification. The pitch is "USB-C for AI"