Why Skills + MCP matter now

Claude has evolved from a chat assistant into a workflow agent. Two capabilities make this work in real organisations:

• MCP (Model Context Protocol): an open standard to connect AI to external systems via tools, resources and prompts exposed by MCP servers.

• Skills: reusable actions that Claude can invoke to perform multi‑step tasks (e.g., “create a sprint plan from Jira and Asana data”, “raise a customer‑credit in Stripe and log the case in HubSpot”).

Together they turn conversation into action—with security, governance and auditability.

Key benefits

• Seamless integrations. Connect Claude to CRMs, project tools and data stores through MCP servers, then wrap common tasks as Skills.

• Streamlined management. Centralise approvals, parameters and access so teams can run the same process reliably.

• Productivity at scale. Automate repetitive work, reduce app‑switching, and capture structured outputs your systems can consume.

How it works

1. Expose your systems via MCP. An MCP server advertises what Claude can do: tools to run functions or APIs, resources to read files or datasets, and prompts to standardise instructions.

2. Create Skills that call those capabilities. A Skill defines the task, inputs, constraints and expected outputs. It can orchestrate multiple MCP calls.

3. Run Skills inside Claude. Users trigger a Skill in chat or programmatically. Claude executes steps, handles errors, and returns a structured result.

4. Add Computer Use when needed. For legacy desktop steps (e.g., clicking a desktop client), enable Claude’s computer‑use capability to complete the flow end‑to‑end.

Practical implementation steps

1) Choose a candidate workflow

Pick a repetitive, rules‑based task with clear success criteria—e.g., create weekly project status, triage support tickets, produce board‑ready finance summaries.

2) Stand up MCP servers for your tools

Start with high‑impact systems (e.g., Google Drive/OneDrive, Jira/Asana, Notion/Confluence, GitHub, Stripe). Confirm authentication, scopes and data boundaries.

3) Design Skills as reusable playbooks

For each workflow, define:

• Inputs (team, date range, ticket IDs).

• Actions (which MCP tools/prompts/resources to call).

• Outputs (JSON payload, file, dashboard update).

• Guardrails (allowed domains, rate limits, approval steps).

4) Govern access and safety

Map Skills to roles (who can run them), add approval gates for sensitive actions, log every tool call, and store artefacts (prompts, parameters, results) for audit.

5) Pilot, measure, scale

Run a 2–4 week pilot. Track time saved, accuracy, exceptions handled, and user satisfaction. Iterate, then promote to wider use with documentation and training.

Examples you can adapt this quarter

• PMO weekly report: A Skill aggregates Jira/Asana epics, pulls risks from Notion, generates a slide deck and posts it to Teams.

• Revenue operations: A Skill checks overdue invoices in your finance app, emails reminders, updates CRM notes and posts a summary to Slack.

• Service desk triage: A Skill classifies tickets, queries a knowledge base, runs a diagnostic tool via MCP, and drafts responses for human approval.

Success metrics

• Cycle time per workflow run

• % steps executed autonomously vs. requiring approval

• Error/rollback rate per Skill

• User NPS for assisted tasks

• Token & runtime cost per completed workflow

FAQs

How do Skills enhance Claude’s capabilities?
Skills package multi‑step tasks—including MCP tools and prompts—so Claude can execute them consistently with parameters, permissions and audit.

What is MCP in the context of Claude?
Model Context Protocol. It’s an open, interoperable way to connect AI to external tools and data through servers that expose tools, resources and prompts.

Can Claude integrate with other tools?
Yes. Through MCP servers (and, when necessary, computer‑use for desktop steps), Claude connects to SaaS apps, data stores and internal APIs.

Do we need developers to start?
You’ll get the best results with light engineering support to configure MCP servers and define Skills. Non‑technical teams can then run them safely.

How is security handled?
Use least‑privilege tokens, environment‑specific servers, audit logs and approval gates. Keep sensitive operations human‑in‑the‑loop.

External references

• Anthropic: Introducing the Model Context Protocol (MCP) — overview and architecture. Anthropic

• ModelContextProtocol.io — official spec; explains tools, resources, prompts. Model Context Protocol+1

• Claude Docs: Computer Use (for legacy desktop automation). Claude

• Claude Code docs: Connect to tools via MCP. Claude Code

• Anthropic updates (agentic workflows, newer models). Anthropic