MCP
Most AI tools are smart but blind. They do not know what your company decided last Monday, what is drifting in Q3, or what the exec team agreed in Tuesday's standup. In Parallel's MCP server changes that, exposing your world model as context so every agent starts from reality, not a blank slate. No custom integrations. No vendor lock-in. Works across any agent platform you choose.
The Parallel Context Graph exposed to every AI in your stack. Claude, Copilot, ChatGPT, Cursor — all draw from the same always-on organisational memory. One connection. Everything in context. Bundled with the paid tier.
With or without
Jane and Sun both ask their AI the same thing on Monday morning: how are my projects doing? Jane gets a confident paragraph that sounds right. Sun gets a short, slightly inconvenient answer that is right.
Without In Parallel
Her AI sees Linear, Slack, a stale roadmap doc, and a Notion page from three weeks ago. It writes a fluent status update. Two projects are described as on track. Both have slipped. One decision in Tuesday's call already changed the scope.
The reply is well-written. It is also wrong. The board reads it on Thursday.
With In Parallel
Her AI pulls the live plan via MCP: scope, owners, decisions, drift signals. The answer is two sentences. Three projects are healthy. One slipped after Tuesday's scope cut. One is missing an owner.
Less prose. More truth. She drafts the board update by lunch.
Three things that change
01
With plan state in context, the model can do what it is actually good at: surface contradictions, hidden risks, and decisions that were quietly dropped — instead of paraphrasing what everyone already knows.
02
Status reports, board updates, customer follow-ups — the kind of work that used to take half a day — collapse to a one-line request. The first draft is already grounded in what is true today.
03
The plan, what changed, and the open questions are already on the page when the meeting begins. You spend the hour deciding — not reconstructing.
Scoped by workspace
Workspaces are the unit of trust. Each one is a separate MCP endpoint with its own data perimeter — so context can never end up in the wrong prompt.
01
Customer X, Project Y, the board, the exec team. Each gets its own MCP URL, its own audit log, its own permissions — granted to people, not to models.
02
Drop the workspace MCP URL into Claude, Cursor, or Copilot, and only that workspace's plan state — decisions, owners, drift — is reachable. Nothing else leaks in.
03
Customer notes never bleed into a board pack. Confidential exec discussions stay out of partner contexts. Wrong workspace, wrong prompt — simply not possible.
Set it up in five minutes
01
Calendar, email, and the meeting tools your team already lives in. In Parallel starts building shared context from your real work — no migration project.
02
In Claude: Settings → Connectors → Add custom connector. Most other tools (Cursor, Copilot, ChatGPT) have an MCP or custom connector field in the same place.
03
One URL per workspace. Your AI now sees plan state, decisions, owners, and drift signals — scoped to what the asker is allowed to see.
What it doesn't do. It will not make a badly-run programme well-run. It will not replace your project tools. It will not make every model good — but the good ones get sharper.
Works in the AI tools you already use
Connect once. Any MCP-capable assistant, coding agent, or automation platform reads your plan-grounded context — scoped per workspace, governed per role.
AI assistants
AI coding agents
Agent platforms
What makes MCP different
01
Every decision, plan update, and meeting signal captured by In Parallel is accessible via MCP. Your agents get the current state of your business, not last month's export. No copy-paste, no re-briefing, no context lost in translation.
02
Enterprises need software that works across any agent stack they choose. In Parallel's MCP-native architecture makes your world model available wherever MCP is supported, today and as your stack evolves. Vendors that make interoperability hard get dropped. We do not.
03
Most AI deployments hit OpEx budget constraints before they prove value. In Parallel's free notetaker is the entry point: no tokens, no budget approval, no friction. Your world model starts building from day one.
Priced per user. Volume and duration earn the discount.
Plans + everything
€69
per user / month
Diagnostics
Continuous behavioural scoring across every meeting, traceable to transcript evidence.
First run
€25,000
One-off engagement. Full 10-lens analysis, evidence-backed recommendations, board-ready deliverable.
Recurring
€15,000 / quarter
Continuous diagnosis with quarterly refresh, trend analysis, and drift alerts.
Portfolio engagement
Custom
For large organisations, divisions, subsidiaries, and PE portfolios. Cross-entity benchmarking and a dedicated success team.
Bring your team in. Use every surface, including every other team's. No credit card. Notes is free for 20 days.
30-minute demo. We'll show you how meeting signals become a plan that maintains itself.
