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SuperPlan MCP is here!

Planning Layer For Your Agents.

Turn your voice notes, rough docs, and half-baked ideas into clear plans for prototyping and building - so your AI Agents actually know what to make.

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How It Works

Turn your ideas into a plan that ships itself

Plan OnceDispatch Everywhere
01

Ingest Context

3

Dump your raw context—docs, designs, audio dumps. We parse the mess so you don't have to.

Supports
02

Structure the Plan

PLAN_SPEC.MD
PROCESSING

AI converts your raw dumps into structured specs, user stories, and actionable issues.

03

Use Plan as MCP

➜mcp.superplan.md/mcp?planId=FYR-14dec
✓ Dispatched

Send the finalized blueprint to your favorite coding agents to execute without confusion.

Agents
OpenAI icon
SPEC-DRIVEN DEVELOPMENT

Agents Write specs. No surprises.

Structured, behavior-driven docs that agents trust and follow.

Your Input
RawIdeas.md
Voice Memo

thinking we should revamp the onboarding...

Competitive analysis
• competitor:
• current:
• target:
Spec
Specifications
Onboarding.spec
auth-flow.spec
AI Draft

Mobile Onboarding

User Story

Goal

Time
Screens

Acceptance Criteria

GIVEN
WHEN
THEN
AI-Native Issues

Issues designed for autonomous execution.

SuperPlan issues are purpose-built for AI agents. Watch the lifecycle unfold—from planning, through execution, to verified proof.

Scroll to see the lifecycle

1
2
3

Planned

Ready
Subscription Upgrade Flow
Guardrails
Spec matches plan
Audit trail attached
No breaking changes

Scope extracted from Blueprint with technical constraints and context links.

1

Planned

Ready
Subscription Upgrade Flow
Guardrails
Spec matches plan
Audit trail attached
No breaking changes

Scope extracted from Blueprint with technical constraints and context links.

2

Executing

Agent running with automated guardrails. Quality stays consistent.

3

Verified

Issue closed only after PR and logs are verified by the orchestrator.

01

Plan once, execute everywhere

Write your context once, then share it instantly with every agent through the Model Context Protocol.

02

Deterministic plans → Deterministic builds

Clear specifications prevent context bloat and endless iterations. Get to working code faster.

03

One brain, many agents

Cursor, Windsurf, Claude, and any other agent—all working from the same plan. No duplication.

04
explore

Branch, backtrack, experiment

Explore different approaches without losing your way. Your structured plan is always there to guide you back.

What builders ask us

Is this just a prompt wrapper around ChatGPT?+
No. The main output is a reusable product index + thesis that later tools (including your agents) query and build on. It's a structured data layer for your product thinking.
Will this slow me down?+
You'll spend a bit more time upfront answering structured questions, but you save time on rework, re-prompting, and misaligned features. It's 'slow down to speed up'.
How good are the docs really?+
The bar is 'good junior–mid PM quality': explicit assumptions, constraints, and edges; clean enough for agents and humans to act on.
Who is this for?+
Freelancers, vibe coders, PMs, founders, and execs who use AI agents heavily and want a repeatable system, not vibes.
What does it integrate with?+
V0: export out to your tools. Later: MCP server + direct integrations.
How much will it cost?+
Early builder pricing target is roughly $5–12/month with usage-based components; final pricing may move with what people actually use.
v0.1
Missing edge case?
Idea
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