Why flat context systems fail
Dumping everything into one pool feels reasonable, until you watch what it does to your best material.
No hierarchy → volume drowns strategy
Dump 150 pages of product docs next to a 2-page messaging framework and the AI can’t tell strategic weight from sheer volume. Your positioning gets buried in technical noise.
No scoping → everything affects everything
You can’t scope competitive intel to battle cards only, or keep product docs out of marketing emails. Context you need for one type pollutes every other.
No portability → private work loses standards
You can’t combine personal drafts with team-approved brand standards. The choice is full exposure or complete isolation. No layering possible.
Context is a budget, not a pile
Only so much of your material fits in the model’s working window for one piece. Plain retrieval ranks one big pile by similarity and takes the top matches, so the moment you write something product-adjacent, your product docs dominate the mix and your brand voice gets squeezed out. Marcora keeps each kind of context in its own budgeted pool and guarantees every layer and audience is represented.
Marcora runs a separate lookup for each layer and merges them. A loud source in one lane literally cannot spend another’s budget, so adding a giant collection never shrinks what your reference library contributes.
Nothing important gets crowded out
Each layer draws from its own budget, and every audience you target keeps its place, so a loud topic can never sweep the whole window. Your brand voice, a key collection, and the campaign brief all make it in, regardless of how the prompt happens to be worded.
You stop engineering the prompt to coax it out
Whatever you’ve put in a collection or project, and whichever audiences you’ve targeted, are guaranteed to contribute as relevant. The right context from every layer makes it in, automatically.
Tell Marcora who you’re writing for
Define the categories that matter to your business, then declare who a piece is for. Marcora treats your choices as first-class signals, not just words in the prompt, and you can change them anytime.
Add, rename, or delete dimensions and their options anytime, they’re yours, not a fixed taxonomy.
You rarely set these by hand. Ask the Marcora agent, or use your own AI over MCP, and it already knows every dimension you’ve defined, then applies the right ones automatically, on top of plain prompt relevance. Declaring them yourself is there for when you want precise control, not a step you have to clear to get a great draft.
However you start, orchestration runs
Three ways into the flow. Whichever door you come through, the same budgeted orchestration decides what actually reaches the model.
Agent-drivenAsk in plain language, in the app or a connected channel like Slack. The agent chooses what to pull, including live web and connected-tool context, your docs, calls, CRM.
Prefer to drive? Fill in a form and choose it all yourself, the deliverable, your targeting dimensions, which collections, and the project.
Use Claude, ChatGPT, or any MCP client as the intake. It calls Marcora’s tools to pull context directly, or to create content that pulls context as it goes.
See the MCP ServerIt runs on every turn, not just the first draft
Editing with the Marcora assistant? Every follow-up, whether you ask the agent to revise the document directly or just talk through changes, goes through the same orchestration, fresh. It reuses what’s already in the session and pulls in only what’s newly relevant to your latest ask, so the right context keeps surfacing as the work evolves.
Instructions adapt to what you’re making
Generic AI treats every request the same. Marcora shifts what it prioritizes based on the deliverable, no manual prompt engineering required.
Activate context deliberately
Your core brand context stays always-on and clean. Everything else layers on top, included when it helps and kept out when it doesn’t.
Organize specialized materials into optional libraries and include them deliberately, not automatically, so they don’t dilute relevance scoring.
Campaign-specific intelligence that’s additive, not isolating. The brief rides along with every deliverable, while your core brand truth stays accessible via relevance.
Attach existing pieces as reference context. Marcora reads their format, messaging, and tone to inform the new one, so content lineage becomes explicit.
Context isn’t just what you say, it’s how you structure it. Blueprints capture format, flow, and coordination across multiple pieces of a campaign.
Your whole team builds on one context foundation
Context orchestration isn’t a per-seat trick. Your team develops one robust set of context, reachable in the app and through an authenticated MCP server, so everyone’s AI generates from the same truth instead of each person wiring up their own. That shared infrastructure is the advantage that compounds.
How the MCP server worksShared by everyone
Your brand foundation, reference library, and shared collections become a single source of truth. Whether a teammate works in the app or points their own AI at the MCP server, they draw from the same governed context.
Private when it needs to be
Keep a collection private, like transcripts from confidential calls, or work in a project only you can access. That layer stays yours, sitting on top of the shared foundation. The app and the MCP server are both authenticated and scoped to your permissions.
What changes when the system assembles context
Faster creation and better first drafts
Consistency that compounds across the team
You don’t start from a blank page
Give us your website when you sign up. Marcora reads your top 20 pages to seed your reference library, and takes a first pass at your brand foundation and targeting dimensions, the roles, products, and industries you target. You refine from there, you don’t build from zero.
A strong first pass. Every bit of it is yours to edit.
Paste a URL or pull in more of your site anytime.
PDFs, decks, and internal documents.
Ask the agent to ingest from your drives and wikis, like SharePoint, OneDrive, Google Docs, or Notion.
Pipe new sources in automatically, like Gong calls flowing into a collection.
The best demo isn’t watching copy get generated
It’s watching what Marcora assembles before the first word is written.
Frequently asked questions
What is context orchestration, in plain English?
A system that automatically gathers and prioritizes the business information an AI needs, brand voice, positioning, product truth, audience insight, so you don’t paste it into every prompt. More importantly, it layers that context intelligently: foundational truth that’s always on, specialized materials activated deliberately, and campaign-specific intelligence that’s additive rather than isolating.
How is this different from a knowledge base or uploading documents?
A knowledge base stores information in a flat bucket. Context orchestration treats context as layered infrastructure, deciding what to use, when to use it, and how much weight it gets based on the deliverable type, the target audience, and what you’re trying to accomplish. It’s the difference between a pile of files and a systematic foundation.
We already use ChatGPT or Claude. Why add Marcora?
Generic AI tools, even with project features, use flat context pools where everything affects everything. You can’t scope competitive intel to battle cards only, or keep product docs from overwhelming marketing emails. Marcora’s layered system gives you hierarchy, scoping, and portability, so the context you’ve built becomes genuinely reusable infrastructure, not just a bucket of files.
Will this help with messaging consistency across my team?
Yes. Marcora keeps brand voice and strategic messaging always-on, so teammates don’t get different outputs simply because they remembered different context. Junior marketers can produce senior-level work because the system provides institutional knowledge automatically, and everyone works from the same foundational truth even when adding their own.
