Customer 360
The joined record — revenue, contacts, feedback, and work for one account, in one call.
The AIOProductOS MCP
Every tool has an MCP now. Only one sees the whole customer.
That one is the AIOProductOS MCP — a single hosted server that exposes revenue, feedback, work, and code already joined on one customer record. Every tool-scoped MCP sees one silo; this one sees the record they all connect to.
71 tools over one endpoint, your AI can read and act on — from the client you already use. Below: what it does, then how to join every tool MCP to the spine.
Came here from a directory listing? Start here — how connecting works, and 20% off your first three months.
No account, no card, no signup
Don't take this page's word for it. Connect it.
Run it with no credentials and it starts anyway — against a fully seeded showcase workspace, read-only, with a subset of the tools. There's nothing to paste, nothing to cancel, and no email required to see whether the joined record is real.
Every claim on this page is checkable that way in about a minute. Ask it "which paying customers asked for the feature we're building?" — then decide whether one MCP over the whole record beats a dozen over silos.
Your own workspace, with writes and the full tool set, is the same command with a
PRODUCTOS_TOKEN set — or the
hosted endpoint over OAuth, no token pasting at all.
$ npx -y @aioproductoscom/mcp
[productos] No PRODUCTOS_TOKEN — starting in DEMO MODE
[productos] against the Brightline showcase org.
[productos] Read-only, seeded data, no signup.That's the server's actual output, not a mockup.
What the AIOProductOS MCP does
71 tools. Read the record, then act on it.
Not a read-only wrapper — the MCP can change the spine, with state-changing actions landing in review so a human approves before anything ships. Everything is scoped to the connected member's role.
Read
Roadmap & work
Tasks, releases, objectives, sprints, roadmap drift — read the plan and its status.
Insights & demand
Feedback ranked by revenue, scored with your framework — what to build and why.
Analytics
Funnels, retention, feature outcomes — read the numbers behind a decision.
Codebase brain
Repos, modules, dependencies, ownership — the architecture on the same spine.
Revenue
MRR, paying accounts, the money behind a request — computed, not guessed.
Act
Create & update tasks
Turn a decision into work on the board, assigned and linked to its customer.
Capture insights
Log feedback to the spine, joined to the account and feature it's about.
Review AI artifacts
Draft, version, and review PRDs and reviews against your rubric.
Resolve identity
Merge or split end-users and accounts — the customer graph, callable.
Works with any MCP host: ClaudeCursorChatGPTWindsurfClineCodex …any MCP client
Connect any tool
The MCP server list for product teams — and where each one stops.
A Jira MCP sees only Jira. A Notion MCP sees only Notion. An Amplitude MCP sees only Amplitude — useful, but your AI still has to stitch five silos together to answer anything real. Connect each tool to AIOProductOS with a connector, and its data joins the customer record — so one MCP call sees it next to revenue, feedback, and code. One MCP over the whole record, instead of a dozen tool MCPs your AI has to reconcile.
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Jira MCP
What the Jira MCP server lets an AI assistant do, where the Atlassian silo ends, and how a spine-level MCP answers the questions Jira alone can't.
Its scope, and the wall →
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Confluence MCP
What the Confluence MCP gives an AI assistant, the silo wall it hits, and how spine-level MCP access answers what docs alone can't.
Its scope, and the wall →
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Linear MCP
What Linear's MCP server lets an AI assistant do, where its scope ends, and how a spine-level MCP handles the customer side Linear doesn't model.
Its scope, and the wall →
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Notion MCP
What the Notion MCP gives an AI assistant, the flexible-workspace trade-off, and what a spine-level MCP answers that a docs graph can't.
Its scope, and the wall →
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Productboard MCP
What Productboard's Spark MCP gives an AI assistant, the feedback-silo boundary, and the spine alternative for cross-domain product questions.
Its scope, and the wall →
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Amplitude MCP
What MCP access to Amplitude gives an AI assistant, the analytics-silo boundary, and how a spine MCP answers revenue-weighted questions.
Its scope, and the wall →
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GitHub MCP
What the GitHub MCP server lets an AI assistant do, the code-silo boundary, and how spine-level MCP access joins code to customers.
Its scope, and the wall →
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Stripe MCP
What the Stripe MCP lets an AI assistant do with payments and billing, the revenue silo it stops at, and how a spine MCP joins revenue to feedback and work.
Its scope, and the wall →
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Slack MCP
What MCP access to Slack gives an AI assistant, why chat context evaporates, and how a spine keeps decisions attached to work.
Its scope, and the wall →
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Figma MCP
What the Figma MCP server gives an AI assistant — design context, components, variables — where it ends, and how a spine MCP joins design to outcomes.
Its scope, and the wall →
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Playwright MCP
What the Playwright MCP server lets an AI assistant do — drive a real browser, test flows — the QA silo boundary, and how a spine MCP joins bugs to customers.
Its scope, and the wall →
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GitLab MCP
What the official GitLab MCP server lets an AI assistant do across issues, merge requests and pipelines, where the repo silo ends, and what a spine MCP adds.
Its scope, and the wall →
New to the protocol? Start with what MCP actually is — or see why spine MCPs and tool MCPs answer different questions.
FAQ
MCP, answered.
What is the AIOProductOS MCP?
It's a hosted, remote MCP server for product teams — 71 tools over one endpoint that expose the customer record: revenue, feedback, work, and code already joined on one spine. An AI client can read that record and act on it (create tasks, capture insights, review artifacts), scoped to the connected member's role.
Can I try the AIOProductOS MCP without an account?
Yes — with no account, no card and no signup. Run `npx -y @aioproductoscom/mcp` with no PRODUCTOS_TOKEN set and the server starts in demo mode against a fully seeded showcase workspace, read-only, with a subset of the tools. Nothing to paste and nothing to cancel. To use your own workspace instead, set a personal access token, or connect the hosted endpoint at https://platform.aioproductos.com/api/mcp over OAuth 2.1.
What is an MCP (Model Context Protocol)?
MCP is an open standard that lets an AI client — an assistant or agent — call into a tool's data and actions through one consistent interface. Instead of a hard-coded integration, the AI connects to an MCP server and can read or act on whatever that server exposes.
How is a spine MCP different from a single-tool MCP?
A single-tool MCP exposes one tool's silo — a Jira MCP sees Jira, a Notion MCP sees Notion. The AIOProductOS MCP exposes the whole customer record: revenue, feedback, work, and code already joined on one spine. So the AI can answer questions that cross tools — 'which paying customers asked for the feature I'm building?' — in one call instead of one silo at a time.
Which AI clients can use it?
Any MCP-compatible client. There's one-click setup for the common ones — Claude, Cursor, ChatGPT, Windsurf, Cline, and Codex — and the same hosted endpoint works with any other client that speaks the protocol. Because MCP is an open standard, you're not locked to one vendor.
Can I connect my other tools' data too?
Yes — that's the point. A Jira MCP sees only Jira; connect Jira to AIOProductOS with a connector and its data joins the spine, so one MCP call sees it next to revenue, feedback, and code. You get one MCP over the whole record instead of a dozen tool MCPs your AI has to reconcile.