Claude Code Skills vs MCP: When to Use Each for Marketing Automation

MCP gives tool access to agents. Skills give instructions to agents. Understanding when to use each separates marketing operators who build effective AI systems from those who dump context and hope for the best. The distinction matters because context management directly impacts agent performance, response quality, and API costs.

Anthropic released Skills as an open standard on December 18, 2025, following MCP’s November 2024 launch. Both solve the same core problem: AI models are only as good as the tools and context you give them. But they solve different parts of that problem. MCP connects agents to your martech stack. Skills teach agents how to execute your specific workflows using those tools.

TL;DR

MCP (Model Context Protocol) connects AI agents to your martech stack: HubSpot, Google Analytics, Notion, Slack, and more. Skills are folders containing instructions that agents load progressively as needed, reducing context bloat and improving response quality. Use MCP to give agents tool access. Use skills to give agents task-specific workflows. Combine both: connect to your CRM via MCP, then use skills to define exactly how your agent generates weekly reports or creates campaign briefs in your team’s format. Estimated time savings: 15-25 hours per week for a 3-person marketing team.

Key Takeaways

• MCP connects agents to your martech stack (HubSpot, GA4, Notion, Slack) while skills teach agents your specific workflows
• Skills use progressive disclosure: metadata loads at startup, full instructions load only when the agent invokes a specific skill
• MCP requires code to build custom servers while skills require only markdown files with YAML frontmatter
• High-value marketing skills include weekly reporting, competitor tracking, content repurposing, and campaign brief creation
• The combination works best: MCP for CRM and analytics connections, skills for standardized reporting and content workflows
• Skills became an open standard on December 18, 2025, with adoption by Microsoft, OpenAI, Cursor, GitHub, and others
• Estimated time savings: 15-25 hours per week for a 3-person team on reporting, research, and content formatting

What Problem Do MCP and Skills Solve?

AI models score near 100% on academic benchmarks. Real-world performance depends on tools and context. A model asked to review your codebase without access to your codebase returns nothing useful. The same model with file access, code interpreter, and coding standards documentation finds bugs you missed.

MCP emerged in November 2024 to standardize how agents connect to tools. Anthropic describes MCP as the USB-C port of AI applications. Your laptop connects to any device through USB-C. Your AI application connects to any tool through MCP. Without MCP, every AI app would build custom integrations for every tool. Every tool would build custom integrations for every AI app. MCP solves this N×M integration problem.

Skills address a different bottleneck. Most MCP clients load all tool schemas into context at startup. An MCP server with 15 tools loads 15 tool descriptions whether you need them or not. Today, developers routinely build agents with access to hundreds or thousands of tools across dozens of MCP servers. Tool definitions consume excessive tokens, reducing agent efficiency. Skills load metadata at startup and full instructions only when relevant. This progressive disclosure keeps context windows lean.

Action item: Audit your current Claude Code setup. Count how many MCP tools load at startup versus how many you use in a typical session.

How Does MCP Work?

MCP follows client-server architecture. The MCP client lives inside AI applications like Claude, ChatGPT, or Cursor. The client sends requests to MCP servers. Servers respond with tool listings, execute tool calls, and return results. MCP is hosted by the Linux Foundation as of December 2025 and is open to contributions from the entire community.

When you initialize an MCP connection, the client asks the server to list available tools. The server returns tool names, descriptions, and schemas. This information enters the context window immediately. The AI needs this context to understand what tools exist and how to call them.

Most MCP clients load all tool definitions upfront directly into context. Tool descriptions occupy context window space, increasing response time and costs. This becomes problematic when agents connect to dozens of MCP servers with hundreds of tools.

MCP servers contain three types of primitives:

• Tools: Model-controlled executable actions like web search, file read, or API calls
• Resources: Application-controlled data access like databases or document stores
• Prompts: User-controlled pre-configured prompt templates for common tasks

Action item: Check the token count of your MCP tool listings. Run a simple prompt and examine how much context the tools consume before your actual request.

How Do Skills Work?

Skills are folders containing instructions, scripts, and resources that agents load dynamically to improve performance on specialized tasks. The minimum viable skill is a folder with one file: SKILL.md (case-sensitive). That file contains YAML frontmatter (metadata) and a markdown body (instructions). The frontmatter loads at startup. The body loads only when the agent invokes the skill.

The SKILL.md frontmatter requires two fields: name and description. The description determines when Claude uses the skill, so it should include both what the skill does and trigger terms users would mention. Anthropic recommends keeping SKILL.md under 500 lines for optimal performance.

When a task matches a skill description, the agent loads the body. The body contains detailed instructions, workflow steps, and context for that specific task. Claude only sees enough to know each skill exists and when to use it until invocation.

Skills support additional folders beyond the SKILL.md file:

• Reference files: Documentation and background materials the agent reads when needed
• Assets: Templates, examples, and resources
• Scripts: Executable Python, JavaScript, or Bash code the agent runs as tools

The agent accesses these folders as needed during task execution. This means the amount of context bundled into a skill is effectively unbounded since content loads on demand rather than at startup.

Action item: Create your first skill folder with a SKILL.md file. Include a clear description with trigger terms matching how you phrase requests to Claude.

What Is Progressive Disclosure?

Progressive disclosure is the core design principle that makes Agent Skills flexible and scalable. Anthropic describes it like a well-organized manual: start with a table of contents, then specific chapters, then detailed appendix. Skills let Claude load information only as needed.

Level one loads skill metadata at startup. The YAML frontmatter (name and description) enters the context window when the agent initializes. This lightweight approach means you install many skills without context penalty. Claude only knows each skill exists and when to use it.

Level two loads the skill body when invoked. The agent determines a skill matches the current task and reads the SKILL.md content. The detailed instructions, workflows, and examples now guide the specific task.

Level three accesses supporting files as needed. The agent reads documentation from reference files. It loads templates from the assets folder. It executes scripts as tools when deterministic operations or heavy computation is more reliable than token generation. This level has no practical token limit since content loads incrementally.

The contrast with MCP is stark. Most MCP clients load all tool schemas at initialization. A server with 15 tools loads 15 tool descriptions immediately. Anthropic has published guidance on using code execution with MCP to load tools on demand, but this requires additional implementation work.

Action item: Diagram your most complex marketing workflow. Identify which context the agent needs at each step versus which context it needs only at specific decision points.

When Should You Use MCP?

Use MCP when you need to connect agents to external systems. MCP provides the communication protocol between your AI application and tools like Notion, Gmail, Slack, web search, and databases. Without MCP, the agent cannot interact with these systems.

MCP servers exist for most major marketing platforms. HubSpot MCP servers read and update contact records, pull deal data, and trigger workflows. Google Analytics MCP servers fetch performance metrics and audience data. Notion MCP servers include approximately 15 tools for reading, creating, updating, and searching content.

Building custom MCP servers requires code. You write server logic in Python or TypeScript. You define tool schemas. You handle authentication and API interactions. The development effort pays off when you need agent access to proprietary systems or platforms without existing MCP servers.

MCP connections for marketing operators:

• HubSpot or Salesforce for CRM data and contact management
• Google Analytics or Mixpanel for performance metrics
• Slack for team notifications and approvals
• Notion or Airtable for content databases and project tracking
• Gmail for automated outreach and response handling
• Web search for competitive intelligence and research

Time saved: 2-4 hours per week on manual data pulls and cross-platform updates when agents handle routine CRM and analytics queries.

Action item: List the external systems your marketing team uses daily. Check MCP server availability for each. Prioritize connections based on automation potential.

When Should You Use Skills?

Use skills when you need to give agents task-specific instructions for repeatable workflows. Skills define how agents complete work consistently, set quality standards, and establish processes. MCP tells agents what tools exist. Skills tell agents how to use those tools for your specific needs.

Creating skills requires only markdown. Write SKILL.md files describing your workflow with YAML frontmatter and instructions. No code necessary for basic skills. A marketer without programming experience creates skills as easily as a developer. For advanced functionality, you attach executable scripts that Claude runs as tools.

Anthropic provides pre-built skills for common document tasks: DOCX (Word documents with tracked changes and formatting), PPTX (PowerPoint presentations with layouts and charts), XLSX (Excel spreadsheets with formulas and data analysis), and PDF (form filling, text extraction, merging). These are available to Pro, Max, Team, and Enterprise users.

High-value skills for marketing operators:

• Weekly reporting skill: Pull data from analytics MCP, format into your standard template, highlight anomalies, suggest optimizations. Time saved: 3-4 hours per week.
• Competitor analysis skill: Search web for competitor updates, extract pricing and positioning, update your tracking spreadsheet. Time saved: 2-3 hours per analysis.
• Content repurposing skill: Take a blog post, generate LinkedIn post, Twitter thread, email newsletter section, all in your brand voice. Time saved: 1-2 hours per piece.
• Campaign brief skill: Gather requirements through questions, output in your team’s standard format with all required sections. Time saved: 30-45 minutes per brief.
• UTM builder skill: Generate tracking URLs following your naming conventions, validate parameters, output to spreadsheet format. Time saved: 15-20 minutes per campaign.

The Notion example illustrates the distinction. Notion’s MCP server provides tools to create pages, update content, and search databases. But the MCP server does not know your specific page templates, which sections belong in your campaign briefs, or your team’s documentation standards. Skills provide that procedural knowledge.

Action item: Calculate time spent on your top 5 repetitive marketing tasks. Prioritize skill creation by hours saved per week.

How Do Skills and MCP Work Together?

The optimal setup combines MCP for tool access with skills for task guidance. Connect to Notion via MCP. Define how to use Notion for your workflows via skills. The agent has both capability (tools) and direction (instructions).

Anthropic explicitly states that MCP and skills are complementary. MCP provides secure connectivity to external software and data. Skills provide the procedural knowledge for using those tools effectively. Partners with strong MCP integrations benefit most from adding skills.

Consider a campaign brief workflow. The MCP connection to Notion provides tools to create pages, add content blocks, and organize in databases. The skill defines the brief template: objective section, target audience section, key messages section, channel requirements section. The skill also instructs the agent to use web search MCP for competitive research before completing the brief.

This combination prevents two failure modes. Without MCP, the agent lacks Notion access regardless of how good your instructions are. Without skills, the agent has Notion access but no guidance on your specific templates and workflows. Both components contribute to successful automation.

Skill and MCP pairing examples for marketing:

• Gmail MCP + outreach sequence skill for personalized email campaigns with your templates
• Analytics MCP + reporting skill for weekly performance summaries in your preferred format
• CRM MCP + lead scoring skill for qualification workflows using your criteria
• Web search MCP + competitive analysis skill for market research with specific data points
• Notion MCP + content calendar skill for editorial planning following your process

Action item: Map your existing MCP connections to potential skills. Identify which connections lack task-specific guidance that skills would provide.

What Does a Marketing Skill Look Like?

A practical marketing skill shows the structure in action. This example creates campaign briefs with consistent formatting and required sections.

The SKILL.md file structure:

---
name: campaign-brief-creator
description: Create campaign briefs with standard sections and formatting. Use when user mentions campaign brief, creative brief, marketing brief, or asks to document a campaign.
---

The body contains instructions:

# Campaign Brief Creator

## Instructions

When creating a campaign brief:

1. Gather required information through questions if not provided:
   - Campaign objective and success metrics
   - Target audience with demographics and psychographics
   - Key messages (limit to 3)
   - Channels and tactics
   - Timeline and budget
   - Stakeholders and approval process

2. Structure the brief using this format:
   - Executive Summary (2-3 sentences)
   - Objective and KPIs
   - Target Audience
   - Key Messages
   - Channel Strategy
   - Timeline
   - Budget Allocation
   - Success Metrics

3. Before finalizing, verify:
   - All sections complete
   - Metrics are specific and measurable
   - Timeline includes key milestones
   - Budget totals match stated amount

## Quality Standards

- Executive summary must state objective, audience, and primary channel
- Each key message limited to one sentence
- Timeline must include start date, end date, and at least 3 milestones
- Budget section must show percentage allocation by channel

This skill triggers when users mention campaign briefs. Claude follows the structured process without you repeating instructions each time. The skill compounds value across every brief you create.

Here is a second example for weekly reporting:

---
name: weekly-performance-report
description: Generate weekly marketing performance reports. Use when user mentions weekly report, performance summary, marketing metrics, or asks for campaign results.
---

# Weekly Performance Report Generator

## Instructions

1. Data collection (use analytics MCP):
   - Pull traffic metrics: sessions, users, bounce rate, time on site
   - Pull conversion metrics: goal completions, conversion rate by channel
   - Pull campaign metrics: spend, clicks, impressions, CPA by campaign
   - Compare to previous week and same week last year

2. Analysis requirements:
   - Identify top 3 performing channels by conversion rate
   - Flag any metric with >20% week-over-week change
   - Calculate blended CPA across all paid channels
   - Note any campaigns exceeding target CPA by >15%

3. Report structure:
   - Executive Summary (3 bullets: wins, concerns, recommendations)
   - Traffic Overview (table with WoW and YoY comparison)
   - Conversion Performance (by channel with trend arrows)
   - Paid Media Summary (spend, results, efficiency metrics)
   - Action Items (specific next steps with owners)

4. Formatting standards:
   - Use percentage changes with directional arrows (↑↓)
   - Round currency to nearest dollar
   - Include sparkline descriptions for trends
   - Bold any metric flagged for attention

## Output Format

Markdown document ready for Notion or Google Docs paste.
Include a Slack summary version (5 lines max) at the end.

This reporting skill eliminates the weekly scramble to pull data from multiple platforms and format it consistently. The agent handles data collection and formatting while you focus on insights and decisions.

Action item: Create a SKILL.md for your most repeated marketing task. Test it by asking Claude to perform the task and verify it follows your process.

What Are the Key Differences?

MCP and skills differ in context loading behavior. Most MCP clients load all tool schemas at startup. Every tool description enters the context window when the server initializes. Skills load only YAML metadata at startup. Full instructions load progressively when the agent invokes a specific skill.

MCP and skills differ in creation requirements. Building custom MCP servers requires code in Python, TypeScript, or other supported languages. You handle API authentication and define tool schemas programmatically. Creating custom skills requires only markdown with YAML frontmatter. Write plain English instructions. Advanced skills optionally include executable scripts.

MCP and skills differ in what they provide. MCP provides secure connectivity to external software and data. Skills provide procedural knowledge for using those tools effectively. Anthropic explicitly states these are complementary: partners with strong MCP integrations benefit most from skills.

MCP and skills differ in adoption status. MCP launched November 2024 and achieved wide adoption within months. Anthropic donated MCP to the Linux Foundation on December 9, 2025. Skills became an open standard on December 18, 2025, with immediate adoption by Microsoft (VS Code, GitHub), OpenAI (Codex), Cursor, Goose, and Amp.

Aspect	MCP	Skills
Purpose	Tool access and data connectivity	Procedural knowledge and workflows
Context loading	All tools at startup	Progressive as needed
Creation method	Code required (Python/TypeScript)	Markdown with YAML frontmatter
Open standard	November 2024, Linux Foundation	December 2025, agentskills.io
Token efficiency	Lower (loads everything upfront)	Higher (loads on demand)

Action item: Evaluate your current context window usage. Calculate potential token savings from converting static instructions to progressive skills.

How Do You Structure Effective Skills?

Effective skills follow a consistent structure. The SKILL.md file (case-sensitive) contains YAML frontmatter with metadata and a markdown body with instructions. Supporting files extend capability with documentation, templates, and executable code.

Frontmatter requires two fields: name and description. The name identifies the skill in logs and debugging. The description triggers skill loading when tasks match. Write descriptions that answer two questions: What does this skill do? When should Claude use it? Include specific capabilities and trigger terms users would mention.

Good description example: “Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.”

The body contains workflow instructions. Break complex tasks into numbered steps. Specify decision criteria at branch points. Include quality standards and output formats. Reference supporting files when the agent needs additional context. Keep SKILL.md under 500 lines for optimal performance.

Skill folder structure for marketing tasks:

campaign-brief-creator/
├── SKILL.md
├── brand-guidelines.md
├── brief-template.md
├── examples/
│   ├── product-launch-brief.md
│   └── seasonal-campaign-brief.md
└── scripts/
    └── fetch-competitor-data.py

The agent loads SKILL.md body when creating campaign briefs. It reads brand guidelines when checking brand alignment. It uses the brief template for structure. It reviews examples for quality reference. It runs the competitor script when the brief requires market context.

Action item: Create a skill folder structure for your highest-value marketing workflow. Write the SKILL.md file with a description containing trigger terms matching how you phrase requests.

What Is Context Rot and How Do Skills Prevent It?

Context rot occurs when irrelevant information in the context window degrades agent performance. Large language models process all context when generating responses. Irrelevant context competes with relevant context for attention. Performance suffers as context windows fill with noise.

MCP contributes to context rot through upfront tool loading. A server with 20 tools loads 20 tool descriptions at initialization. If your task requires only 2 tools, 18 tool descriptions consume tokens without contributing to task completion. Those tokens add cost and reduce performance.

Skills prevent context rot through progressive disclosure. Metadata loads at startup but consumes minimal tokens. Full instructions load only when matched to tasks. Supporting files load only when specifically needed. Irrelevant content never enters the context window.

The performance impact compounds in complex workflows. An agent with 5 MCP servers might load 50+ tool descriptions at startup. Add a lengthy system prompt. Add conversation history. The context window fills before meaningful work begins. Skills keep context lean by loading incrementally.

Cost implications follow the same pattern. Token usage determines API costs. Unnecessary context wastes money on every request. Skills reduce per-request token counts by loading context on demand rather than upfront. The savings multiply across thousands of agent interactions.

Action item: Compare response quality on a complex task with all context loaded upfront versus progressively disclosed. Note differences in accuracy and relevance.

How Do You Build a Marketing AI Stack with Skills and MCP?

The marketing AI stack combines MCP connections for data access with skills for workflow execution. This architecture separates tool capability from procedural knowledge, making both easier to maintain and extend.

Layer 1: Data connections via MCP. Connect to your CRM (HubSpot, Salesforce), analytics (GA4, Mixpanel), project management (Notion, Asana), communication (Slack, Gmail), and ad platforms. Each connection gives Claude read and write access to that system.

Layer 2: Workflow skills for each marketing function. Create skills for content creation, campaign management, reporting, competitive analysis, and customer research. Each skill defines how to use the MCP tools for specific tasks.

Layer 3: Orchestration through Claude Code or your preferred agent environment. The agent matches user requests to skills, invokes relevant MCP tools, and follows skill instructions to complete tasks.

Example marketing stack configuration:

MCP Connections:
├── hubspot-mcp (CRM data, contact management)
├── google-analytics-mcp (traffic, conversions, audiences)
├── notion-mcp (content database, project tracking)
├── slack-mcp (notifications, approvals)
└── web-search-mcp (research, competitive intel)

Skills:
├── weekly-performance-report/
├── competitor-tracking/
├── content-repurposing/
├── campaign-brief-creator/
├── lead-scoring-analysis/
└── utm-generator/

This stack handles 80% of routine marketing operations. The agent pulls CRM data via HubSpot MCP, formats it using the reporting skill, posts summaries to Slack via Slack MCP. No manual data exports or formatting required.

Estimated time savings for a 3-person marketing team: 15-25 hours per week on reporting, research, and content formatting tasks.

Action item: Map your current marketing tech stack. Identify which systems need MCP connections and which workflows need skills. Start with one MCP + one skill combination.

Final Takeaways

MCP connects agents to your martech stack (HubSpot, GA4, Notion, Slack) while skills provide the procedural knowledge for executing your specific workflows using those tools. Use both together for maximum automation.

Progressive disclosure loads only skill metadata at startup. Full instructions, reference files, and scripts load only when the agent invokes a specific skill. This prevents context rot and keeps API costs predictable.

Skills require only markdown with YAML frontmatter. Marketing operators create custom skills documenting their reporting templates, content formats, and campaign processes without any programming.

High-value marketing skills include weekly performance reporting (3-4 hours saved), competitor analysis (2-3 hours), content repurposing (1-2 hours per piece), and campaign briefs (30-45 minutes each). Prioritize by hours saved per week.

Agent Skills became an open standard on December 18, 2025, with immediate adoption by Microsoft, OpenAI, Cursor, and GitHub.