Claude Plugins vs Skills vs MCP

In less than a year, Anthropic shipped three separate extension mechanisms for Claude — MCP in November 2024, Plugins in October 2025, Skills in October 2025 — and the confusion followed quickly. Most people treated them as competing options for roughly the same job, installed all three without a clear model for what each one was for, and ended up with sessions that were heavier and less predictable than before. The confusion has a specific cause: Plugins, Skills, and MCP are not three parallel choices. They are three layers of the same stack, solving three genuinely different problems.

The clearest one-line version: Skills teach Claude how to work. MCP gives Claude access to external systems. Plugins bundle both together into something you install once. A Skill can use an MCP tool. A Plugin can contain a Skill. They’re complementary, not competing — and understanding which layer solves which problem is what makes the whole stack actually useful rather than just heavy.

Skills: Teaching Claude How to Work

A Skill is a folder of instructions that Claude reads when a task calls for it. Each one contains a SKILL.md file — YAML metadata at the top describing when to use it, followed by markdown instructions — and can optionally include reference documents, scripts, and template files. Anthropic describes them as “onboarding guides,” which is an accurate framing: you’re writing the documentation you’d give a new hire who needs to learn your team’s specific processes, brand voice, or workflow patterns.

The key technical advantage is how they load. Skills use only 30–50 tokens of overhead until the moment they’re actually needed — at which point Claude pulls the relevant instructions into context for that specific task. This means an organisation can have fifty Skills available without meaningfully slowing sessions down. Compare that to MCP servers, which front-load all their tool definitions into context at session start regardless of whether they’re used.

• Use Skills for recurring, expertise-heavy workflows: brand voice guidelines, SEO content brief formats, contract review patterns, cold-outreach playbooks, reporting templates
• Use Skills for procedural knowledge a senior team member carries in their head — write it once, reuse it everywhere, iterate it weekly without touching anything else in the stack
• Skills are cross-platform: the same SKILL.md structure works across Claude, Codex, Gemini CLI, and other compatible tools
• Skills have the lowest cost of being wrong: if a Skill turns out to be insufficient for a task, you’ve lost ten minutes of markdown writing rather than a week of server development
• Skills cannot reach external systems on their own — they encode how to do something, not the ability to access a live database or API

Start with Skills. They have the lowest cost of being wrong. If a Skill turns out to be insufficient, you’ve lost ten minutes of markdown writing, not a week of server development.— systemprompt.io, Claude extension decision guide

MCP and Connectors: Giving Claude Access to External Systems

The Model Context Protocol is an open standard — not a Claude-specific proprietary system — for connecting LLMs to external tools and data sources. Anthropic open-sourced it in November 2024, OpenAI adopted it in March 2025, and Google DeepMind followed in April 2025. The “USB-C” analogy circulates for a reason: build an MCP server once and it works with Claude, ChatGPT, Gemini, or any other tool that speaks the protocol.

Within Claude’s apps specifically (claude.ai, Cowork, Claude Desktop), MCP shows up as Connectors — Anthropic’s packaging of remote MCP servers for common services like Microsoft 365, Google Drive, Slack, GitHub, and Linear. When you enable a Connector, Claude can actually read your emails, access your files, and take actions in those services on your behalf. The Connector is Claude’s wrapper around the underlying MCP server; MCP is the open protocol that makes the connection possible at all.

• Use MCP/Connectors when Claude needs to reach something external and live: querying a database, posting to Slack, reading files from Google Drive, interacting with GitHub, pulling data from a CRM
• The key trade-off is context weight. A typical five-server MCP setup with 58 available tools uses approximately 55,000 tokens before any conversation begins. GitHub’s official MCP server alone uses tens of thousands of tokens just describing its capabilities
• Anthropic’s Tool Search feature reduces this by roughly 85% through on-demand tool discovery, but most setups don’t use it yet
• MCP doesn’t make Claude smarter about how to work — it gives Claude access to more things. The procedural “how-to-work” intelligence is still what Skills encode

Plugins: The Bundle That Contains Both

A Plugin is not a third category alongside Skills and MCP — it’s a packaged combination of both, plus slash commands and agents, distributed via a marketplace for one-click installation. If Skills are individual recipe cards and MCP servers are the kitchen plumbing, a Plugin is the full kitchen, stocked and ready to cook. Anthropic launched 11 official Plugins at release covering legal, sales, finance, marketing, and data analysis workflows; a Plugin marketplace launched in February 2026.

One concrete example of what a Plugin actually bundles: a legal Plugin ships with Skills for NDA review workflows and document analysis, Connectors for document management integrations and DocuSign, slash commands like /review-contract, and sub-agents the parent Plugin can delegate specific tasks to — all registered and configured in a single install step rather than assembled piece by piece manually.

• Use Plugins when you want a ready-made, job-specific toolkit rather than building one skill and one connector at a time
• Use Plugins when sharing a workflow package with a team — one install gives everyone the same Skills, slash commands, and connector requirements
• Build a Plugin when you’ve assembled a working combination of Skills and MCP configurations for a specific domain and want to package it for reuse or distribution
• Plugins are not a shortcut around understanding Skills and MCP — what’s inside a Plugin is exactly the same as building those layers manually, just packaged for convenience

Side-by-Side Comparison

Decision Framework: Which One Do You Actually Need?

How They Work Together

The most common and effective pattern is using Skills and MCP together rather than choosing between them. A Skill can call an MCP tool mid-task — for example, a content-brief Skill could pull real-time keyword data from a connected SEO tool via MCP, apply your specific briefing format and client rules from the Skill’s instructions, and produce the output without you needing to load everything manually into context.

• Perplexity or research → Claude with a writing Skill: gather sourced research in Perplexity, then hand off to Claude with a Skill encoding your specific content format and brand voice
• MCP connector for live data + Skill for domain logic: pull a live HubSpot deal via Connector, apply a Skill’s deal-analysis and summary format
• Plugin as the wrapper: once that combination is working reliably, package both the Skill and the MCP configuration into a Plugin for the rest of the team to install in one step

Understanding how Claude compares to other AI platforms as a whole — not just its extension stack — is covered in our detailed breakdown of Claude vs ChatGPT vs Gemini vs Perplexity, which walks through task-by-task comparisons across SEO, copywriting, coding, research, and more.

Practical Use Cases for Marketing Teams

A digital marketing agency’s use of this stack looks different from a software development team’s — and that specificity matters. Here’s what each layer typically handles in a marketing context:

• Skills for marketing: SEO content brief format (enforced across every brief), brand voice guidelines (client-specific, swapped per project), cold-outreach templates and sequence logic, campaign reporting format, monthly client update structure
• MCP/Connectors for marketing: live Google Search Console data for a technical SEO audit, reading Slack threads for context during a campaign debrief, accessing a Google Drive folder of client assets, pulling a CRM contact record before an outreach draft
• Plugins for marketing: a full SEO audit Plugin that bundles a content-brief Skill, a screaming-frog-parse Skill, and a Google Search Console Connector all in one installable package — then shared across the whole agency team

Mistakes That Make the Stack Confusing

• Treating Skills, MCP, and Plugins as three competing answers to the same question rather than complementary layers
• Using MCP to encode a workflow or process — that’s a Skill’s job; MCP doesn’t make Claude smarter about how to work, only about what it can access
• Adding too many MCP servers at once without Tool Search, letting context overhead bloat sessions before any real work begins
• Building a complex MCP server for something a ten-minute Skill file would have solved correctly
• Skipping Skills entirely and only using Plugins, which means you understand the package but not the layers inside it
• Assuming Plugins can be configured to fit non-standard workflows without understanding what Skills and MCP configurations they contain

Final Thoughts

The confusion between Plugins, Skills, and MCP traces almost entirely to treating them as alternatives rather than layers. Once the actual shape is clear — Skills for procedural expertise, MCP for live external access, Plugins as the distributable bundle of both — each one becomes straightforward to reach for at the right moment.

Start with Skills, since they’re the lowest-cost way to encode the workflows and domain knowledge your team repeats every week. Add MCP/Connectors when a task genuinely requires live data or an action in an external system — not as a substitute for Skills, but as the layer that gives the stack real reach. Use Plugins when you want a job-specific toolkit assembled for your team rather than built piece by piece, or when you’re ready to share a working combination of Skills and connectors with everyone at once.

Most marketing teams find that two or three well-written Skills and one or two focused Connectors handle the majority of recurring work — and that starting there, rather than with a full marketplace Plugin, is how you actually learn what the stack can do for your specific workflows.