At a Glance
| Term | What It Means |
| Integration / connector | A built or pre-built link between two apps so data or actions flow between them automatically |
| iPaaS | A platform (Zapier, Workato, Make) that ships many pre-built connectors instead of custom point-to-point code |
| MCP (Model Context Protocol) | An open standard, released by Anthropic on November 25, 2024, for connecting AI applications to external tools and data sources |
| MCP governance | Donated by Anthropic to the Agentic AI Foundation, a Linux Foundation directed fund, on December 9, 2025 |
Short Verdict
“Integrations” and “connectors” are the decades-old problem of getting software to talk to other software; MCP is a 2024 attempt to solve a newer, narrower version of that same problem specifically for AI assistants and agents. The two are related but not interchangeable — an iPaaS tool like Zapier connects apps to each other, while MCP standardizes how an AI model connects to tools and data in the first place. Both matter for the same underlying reason: bespoke, one-off integrations don’t scale, and a shared standard means something gets built once and reused everywhere.
Integrations and Connectors, in Plain Terms
An integration is simply a link that lets two pieces of software exchange data or trigger actions in each other — a new row in your CRM creating a task in your project-management tool, or a form submission landing in a spreadsheet. Historically, building these required custom, point-to-point code for every single app pair, which doesn’t scale once you have more than a handful of tools. That’s the gap an iPaaS (integration-platform-as-a-service) fills: as Zapier’s own explainer defines it, iPaaS is “a cloud-based software service solution that lets organizations connect different applications” across cloud, on-premises, and hybrid environments, typically through pre-built connectors and low/no-code tools rather than hand-coded integrations. Zapier itself is a familiar example — its current pricing runs from a Free plan (100 tasks/month, unlimited workflows) up through Professional at $19.99/month billed annually, Team at $69/month billed annually, and a custom Enterprise tier, per Zapier’s own pricing page. Workato, by contrast, markets itself as an “Enterprise iPaaS” aimed at larger organizations automating workflows like Salesforce-to-NetSuite quote-to-cash processes, serving both IT and what it calls “citizen integrator” business users, per its own documentation.
What MCP Actually Is
The Model Context Protocol was announced and open-sourced by Anthropic on November 25, 2024, created by Anthropic engineers David Soria Parra and Justin Spahr-Summers. Per Anthropic’s own announcement, even the most capable AI models are “cut off from data trapped in information silos and legacy systems,” and historically every new data source needed its own bespoke integration — which doesn’t scale any better for AI assistants than it ever did for regular software. MCP’s pitch is to replace that fragmentation with what Anthropic calls “one protocol” and a “universal, open standard” for connecting AI systems to data sources, tools, and workflows.
The current official definition, from the independently-governed modelcontextprotocol.io documentation site, puts it simply: MCP “is an open-source standard for connecting AI applications to external systems.” The docs use a specific, official analogy — not just press shorthand — stating directly: “Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems.”
How It’s Built: Hosts, Clients, and Servers
Per MCP’s official architecture specification, the protocol follows a client-host-server model built on JSON-RPC. The host is the application a person actually uses (Claude Desktop, for example), which creates and manages clients and enforces security policy and user consent. The client is created by the host, with a strict one-to-one relationship to a single server, handling protocol negotiation and keeping servers isolated from each other. The server exposes “resources, tools and prompts” — the protocol’s three core primitives — and can run locally or remotely. A key design principle stated directly in the spec: “Servers should not be able to read the whole conversation, nor ‘see into’ other servers” — the host keeps full conversation context, and servers only see what’s relevant to their own job. In practice, tools are actions the model can call, resources are contextual data the application can read, and prompts are reusable templated instructions — all negotiated when a session starts.
Why It Matters — and Who’s Adopted It
The official docs frame the benefit differently depending on audience: for developers, MCP “reduces development time and complexity” when building or integrating with an AI application; for AI applications themselves, it provides access to “an ecosystem of data sources, tools and apps”; for end users, it means more capable assistants that can access their data and take action on their behalf. The tagline the docs use for the ecosystem effect is “build once and integrate everywhere” — instead of every AI vendor building a custom Slack integration, a Google Drive integration, and a GitHub integration from scratch, one MCP server for each can work across any MCP-compatible AI application.
Adoption moved quickly after the November 2024 launch: Cursor added MCP server support in February 2025, Microsoft brought MCP into Copilot Studio and Cloudflare enabled customers to deploy remote MCP servers by around April 2025, and OpenAI added MCP support to its Agents SDK that same month, with modelcontextprotocol.io’s current documentation now listing ChatGPT among MCP-supporting AI assistants and linking to OpenAI’s own MCP developer docs. Visual Studio Code and Cursor are both listed as MCP-supporting development tools on the current official docs. One figure we’re deliberately not citing precisely: the number of community-built MCP servers now in existence. Estimates circulating across different third-party sources range anywhere from roughly 1,400 to over 11,000, depending on methodology and date — none of that is an Anthropic- or modelcontextprotocol.io-published figure, so treat any specific server count you see elsewhere as a rough, fast-moving estimate rather than a settled number.
The most significant recent change is governance, not adoption: on December 9, 2025, Anthropic donated MCP to the Agentic AI Foundation (AAIF), described as a directed fund under the Linux Foundation, with Anthropic, Block, and OpenAI as founding co-sponsors and Google, Microsoft, AWS, Cloudflare, and Bloomberg named as supporters. MCP’s existing maintainer structure and technical direction are stated to remain unchanged under this arrangement — the Linux Foundation’s role is custodial, not directive. This is independently corroborated by outside reporting beyond Anthropic’s own channels, which is part of why it’s credible as more than a one-source claim.
Bottom Line
Integrations and iPaaS tools solve how regular software talks to other software; MCP solves the newer, specific problem of how an AI assistant talks to your tools and data without a bespoke integration for every single one. Less than two years after its November 2024 launch, MCP has been adopted across a wide swath of the AI tooling landscape and transitioned to vendor-neutral, Linux Foundation-adjacent governance — a sign it’s being treated as infrastructure rather than a single vendor’s side project. If you’re building or buying AI tooling today, whether a connector supports MCP is a reasonable question to ask, in the same way “does this integrate with Zapier” became a reasonable question for SaaS tools a decade ago.
Sources
- Anthropic — Introducing the Model Context Protocol (original Nov 25, 2024 announcement)
- Model Context Protocol — official introduction (USB-C analogy, ecosystem benefits)
- Model Context Protocol — official architecture specification
- Zapier — What Is iPaaS?
- Zapier — Pricing
- Workato — What Is Workato
- The Batch (DeepLearning.AI) — OpenAI adopts MCP
- Microsoft — MCP in Copilot Studio
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