Lucas Oliveira
Claude Skills and MCP turn AI from a chat toy into a real growth engine by connecting Claude directly to your ad platforms, CRM and analytics. Here is the plain-English setup for automated reporting, lead scoring and campaign audits, plus the mistakes that quietly waste your budget.
It's Monday morning and your best media buyer is copying spend numbers out of Google Ads into a spreadsheet for the fourth client in a row. Three hours later you have a deck nobody reads and the campaign audit that never happened.
The fix is not a smarter model. The bottleneck was never intelligence, it was plumbing. Claude can't see your ad accounts, your CRM or your analytics until something connects them.
That something is MCP (Model Context Protocol, an open standard for plugging tools into AI). Once the pipe exists, Skills are what turn a one-off answer into a repeatable process. Connect first. Encode judgment second.
What you'll be able to do
- Pull a weekly paid-ads report across Google Ads and Meta without opening either interface.
- Score incoming leads against a rubric you wrote once, in plain English.
- Run a scheduled campaign audit that flags wasted spend before a client calls you about it.
- Hand a non-technical marketer a workflow they can trigger with one sentence.
What you need
- A paid Claude plan (entry tier is around $20 a month) or an API key.
- Read-only access to one ad account. Not twelve. One.
- The Claude desktop app for connectors, or Claude Code if the workflow touches files and schedules.
You do not need to be a developer. You need to copy a command from a vendor's own instructions and paste it.
Where people get stuck is authentication: agency-level account access, OAuth permissions that expire, service accounts nobody remembers creating. Budget an afternoon for that part, not the AI part.
What MCP actually is, in plain English
Anthropic published MCP as an open standard on November 25, 2024. Think of it as USB-C for AI tools: one port, and anything following the standard can plug in. An MCP server sits between Claude and a platform, translating requests in both directions.
Three things travel through that port: tools (actions Claude can take), resources (data it can read) and prompts (reusable templates). That's the whole protocol. You can read the specification and its dated revisions yourself.
Why this matters for growth teams: MCP is not an Anthropic-only lock-in. OpenAI publicly committed in March 2025. Google DeepMind followed in April 2025.
Microsoft shipped support across its Copilot tooling during 2025. When three competitors back the same connector standard, what you build on it stays useful.
What a Skill actually is (the part people skip)
Agent Skills shipped on October 16, 2025. A skill is a folder containing a file called SKILL.md. That's it. No build step, no deployment, no vendor portal.
You can write one in a text editor before your coffee goes cold.
What makes them cheap is progressive disclosure. Only the skill's name and description load at startup, roughly 100 tokens each. The full instructions load only when the skill triggers. Bundled scripts and reference files load only when needed.
Translation: you can keep 20 to 50 skills within reach for the token cost of a paragraph. Which means the description field is your routing layer.
"Helps with marketing" will never fire. "Build the Monday paid-ads report from the Google Ads and Meta Ads MCP servers; use when the user asks for a weekly report, spend summary or campaign audit" fires every time.
Your first workflow: the Monday ads report
Step 1: Connect one server
In the Claude desktop app, pick an ads connector from the directory and authorise it with read-only scope. In Claude Code, use the claude mcp add command taken from that server's own README, never from a blog post. Then type /mcp in a session to confirm what's live.
If it won't connect, run MCP Inspector before you blame the model.
Step 2: Verify with one question
Ask: "List the top 5 campaigns by spend in account X for the last 7 complete days, with spend, conversions and CPA." Now open the ad platform and reconcile every number by hand.
If it doesn't match exactly, stop and fix the server. Never build on numbers you haven't verified once.
Step 3: Write the skill
Create a folder, then paste this in as your SKILL.md. The three lines at the top tell Claude when to use the file and which tools it may touch. Everything below is your rulebook.
---
name: weekly-ads-report
description: Build the Monday paid-ads report from the Google Ads and Meta Ads
MCP servers. Use when asked for a weekly report, spend summary or audit.
allowed-tools: mcp__google_ads, mcp__meta_ads, Read, Write
---
## Definitions (never substitute these)
Conversions = platform-reported, 7-day click / 1-day view
Spend = gross media spend, excludes agency fee
CPA = spend divided by conversions, computed by script, never mentally
## Procedure
1. Read the client list from clients.json
2. Pull the last 7 complete days plus the previous 7, aggregated by campaign
3. Flag any campaign where spend moved over 25% or CPA missed target by 20%
4. Write the report to reports/YYYY-MM-DD-client.md
## Guardrails
Read-only. Propose changes, never apply them. If a metric is missing, write
"not available" instead of estimating.Step 4: Run it by hand, then fix the skill
Run it 10 to 20 times manually. Every time something is wrong, fix the skill file, not the prompt. Prompts vanish. Skills compound.
This is the step everyone skips, and it's the difference between a party trick and a system.
Step 5: Schedule it, keep a human gate
Claude Code has a non-interactive print mode that pairs with any scheduler, so the report can be waiting at 7am Monday. Two rules: log everything, and alert if no report exists by 8am, because OAuth tokens expire and jobs fail silently.
And the job writes drafts only. A human approves anything customer-facing.
Here's what this looks like in practice. A three-person agency running 12 client accounts typically spends around six hours every Monday on copy-paste reporting, and only audits accounts when a client complains.
The same team, with one ads server and one skill, ends up reviewing drafts in minutes and running audits on a schedule. That's an illustrative pattern, not a benchmark, but the direction is consistent.
The mistakes that actually cost money
- Tool bloat. Installing 15 MCP servers at once floods context with tool definitions and degrades tool selection. Enable three to five. Add the next one only when you hit a real wall.
- Vague skill descriptions. If yours doesn't name the trigger, the servers involved and the task, it will never fire or it will fire at the wrong moment.
- Metric definition drift. Google Ads "conversions" versus "all conversions," Meta's attribution windows, Google Analytics modelled conversions. If your skill doesn't pin the exact metric and window, your week-over-week comparison is fiction. For how badly this goes wrong when tracking is loose, read these consent mode mistakes.
- Write access on day one. An LLM driving bulk edits is how a $5k/day account becomes a $50k/day account. Read-only for weeks. If you must write: paused or draft status only, hard caps on budget changes, and a human approval step.
- Trusting tool output blindly. Campaign names, UTM parameters and form-fill text are attacker-controlled strings. Read-only scopes, allowlists on what can leave your system, and no auto-sending model output anywhere.
- Automating the artifact, not the decision. A dashboard nobody reads is overhead with extra steps. Automate the alert and the recommended action.
Where to go next
Add skills one at a time, and reuse the same definitions block in each. A lead-scoring skill (CRM data plus a rubric in the skill body) is a natural second build, and it pairs well with proper dead lead reactivation.
A campaign-audit skill should hunt search-term waste, creative fatigue and message match breaks. A funnel diagnostic combines Google Analytics with CRM stage conversion, which is where most demo no-show leaks show up as a number instead of a hunch.
Full documentation lives at Anthropic. Check pricing and limits there before you quote anyone a number, because both move.
You now know enough to build the first one yourself. The hard part isn't the file, it's the metric definitions and the authentication, and those are judgment calls you've already been making by hand for years.
Frequently Asked Questions
Do I need to know how to code to use Claude Skills and MCP? +
No. A skill is a folder with a plain text file inside, and connecting MCP is copying one command or clicking through an OAuth screen. The one thing that does take real effort is authentication: getting read-only access to an agency-level ad account or CRM usually takes longer than the setup itself.
What's the difference between MCP and a Skill? +
MCP is the connection layer. It's how Claude reaches your Google Ads, Meta Ads, CRM or analytics data. A Skill is the instruction layer. It's the written procedure that tells Claude what to do with that data, in what order, using which definitions. You need both for automation, and Skills are the part most teams forget to write.
Is it safe to give Claude access to live ad accounts? +
Yes, if you start read-only and stay there for a while. The real risks are granting write access too early, installing unchecked community servers, and letting attacker-controlled text from campaign names or form fills influence what the agent does next. Verify with one question against the platform UI before you build anything on top of a connection.
How much does this actually cost to run? +
Your Claude subscription is the main cost, and the entry tier is around $20 a month. If you run on the API instead, a mid-tier model costs roughly a few dollars per million input tokens, and cached reads drop to about a tenth of that. A weekly report that ingests a few hundred thousand tokens costs well under a dollar.
