AI is everywhere, and as marketers, we’ve all experimented with using it to draft social posts, brainstorm headlines, or even write the odd blog post. But if you’ve ever found yourself repeating brand guidelines, re-prompting campaign goals, or correcting tone inconsistencies across AI outputs, you’re not alone.
That’s where Model Context Protocols (MCPs) come in. They’re not just for developers or AI researchers; they’re a game-changer for internal marketing teams looking to scale content creation without sacrificing strategy, brand consistency, or quality.
What are model context protocols (MCPs)?
At a high level, MCPs are a way to embed structured context into how AI models interact with your team. Think of them as a persistent brain for your brand: a set of instructions, data, and behavior guidelines that the model can remember and apply across tasks.
Instead of re-prompting the AI every time you want it to “sound like your brand” or “focus on a specific persona,” you load that context once, and it stays with the model throughout your workflow.
Why MCPs matter for internal marketing teams
Most marketing teams juggle a lot: campaigns, content calendars, social media, email sequences, product updates, and more. AI can help speed up many of these tasks, but often with limitations:
- Content lacks brand voice consistency.
- Switching between campaigns or clients confuses models.
- Writing the same prompt instructions over and over.
With MCPs (or tools that simulate them), all these limitations can be addressed.
Brand voice becomes built-in
Create a tone protocol that includes voice traits, words to use (and avoid), and brand personality pillars. Then any AI-generated content stays in character, whether it’s writing a LinkedIn post or a product page intro.
Campaigns stay on-message
When launching a campaign, define a “context bundle”: objectives, target audience, product details, themes, and messaging priorities. The AI can then reference that bundle across content pieces without you needing to re-explain it.
Multiple personas, no confusion
Work with different customer personas across industries. With MCP-style memory, the AI doesn’t mix up the CIO with the social media manager. It knows who it’s talking to.
Spend more time creating, less time correcting
By front-loading the strategic context, you can dramatically reduce the need for rework. The AI gets it right (or very close) on the first try.
How to use MCPs in your workflow
You don’t need to build a custom AI system from scratch to benefit from MCPs. Here’s how you can approach it using tools and techniques available today:
1. Create reusable brand context packs
Include:
- Brand voice guidelines
- Key messaging frameworks
- Common product descriptions
- Do’s and don’ts for content
These can be loaded into tools like custom GPTs or structured into prompt templates.
2. Set campaign context at the start
For every major campaign, define:
- Campaign name and goal
- Audience persona
- Messaging pillars
- Channels and tone
Then load this into your AI tools to guide outputs.
3. Use AI tools that support persistent context
Some platforms that help simulate MCPs:
- Custom GPTs (via OpenAI): set instructions and memory
- Notion AI: maintain brand tone and knowledge across docs
- Jasper / Copy.ai: input style guides and brand voice presets
- Claude (Anthropic): persistent memory and long-form context
If you’re using APIs, you can build even more customized workflows that hold and switch contexts as needed.
Is it worth it for your team?
We’d say: if your team creates content for more than one audience, across more than one channel, it’s worth exploring.
Especially if you:
- Manage multiple campaigns in parallel
- Have to enforce strict brand voice guidelines
- Want to scale output without scaling headcount
- Use AI regularly in your process, but feel like you’re babysitting it
MCPs are like hiring an assistant who remembers everything – instantly.
Final thoughts
Model Context Protocols may sound technical, but at their core, they’re about making AI work more like a smart team member than a task rabbit. For internal marketing teams juggling deadlines, messaging, and channels, they can be the key to unlocking smarter, faster, more strategic use of AI.
We’re still evolving our use of MCPs, but the benefits are clear: less manual prompting, better brand alignment, and faster content cycles. And as AI tools continue to evolve, this kind of structured, strategic context management will become a baseline, not a bonus.
