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The context layer for AI-first teams

Discuss as a team.
Ship specs to your
coding agent.

Contexire captures every product decision from your team's conversations and turns them into structured, living specs that Cursor, Claude Code, and Copilot can actually execute on.

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Works with Cursor
Works with Claude Code
Works with Copilot
MCP native
Persistent Product Memory
Real-time Team Sessions
MCP Server Export
Auto-generated Specs
AI That Participates
Mermaid Diagrams
Gap Detection
Decision Logs
Cross-session Memory
Persistent Product Memory
Real-time Team Sessions
MCP Server Export
Auto-generated Specs
AI That Participates
Mermaid Diagrams
Gap Detection
Decision Logs
Cross-session Memory

The Problem

Decisions happen in chat.
Agents need structured context.

The bottleneck isn't your coding agent. It's everything that happens before you open Cursor.

Hours
lost every week re-explaining past decisions

Decisions die in chat

Two-hour Slack debate about auth strategy. The decision gets buried in a thread. Next sprint, the same question resurfaces because nobody can find it.

3 lines
of context most coding agents actually receive

Agents fly blind

Cursor and Claude Code are powerful — but only as good as the context you give them. Most teams paste a few sentences and hope for the best.

Day 1
is when most specs stop being accurate

Specs rot instantly

You wrote a PRD once. It was outdated by Tuesday. Real decisions live in conversations that nobody extracts or maintains.

How It Works

Three steps.
Discussion to deployable spec.

01
Discuss with your team + AI

Start a session. Invite teammates. AI joins as a participant — asking follow-ups, catching gaps, and pushing back before open questions become bugs.

Auth Session
SSam · 2m ago
JWT with short-lived access tokens. Refresh in httpOnly cookies for web. What about mobile?
RRiya · 1m ago
Keychain on iOS, Keystore on Android. Same refresh flow, different storage layer.
AIContexire · just now
Good call. I updated the auth spec with both strategies and added silent token rotation. Want me to flag CSRF implications for the cookie approach?
02
AI builds a living spec

As you talk, AI extracts decisions, schemas, architecture choices, and constraints into a structured spec that updates in real time.

Live Spec · Authentication
strategyJWT + rotating refresh tokens
web_storagehttpOnly cookie, SameSite=Strict
mobile_iosKeychain via SecureEnclave
mobile_androidAndroid Keystore System
access_ttl15 minutes
refresh_ttl30 days (rotate on use)
statusdecided
03
Export to your coding agent

One click turns your spec into an MCP server or markdown bundle. Your coding agent finally knows what to build — and why.

Export to Agent
Choose format
MCP ServerMarkdownJSON
// .cursorrules - auto-generated
Auth: JWT + httpOnly cookies
Mobile: Keychain / Keystore
Access TTL: 15min
Rotation: on each refresh
// + 47 more decisions loaded
50 decisions · 3 schemas · 12 constraints loaded

Features

Everything the context layer needs.

Persistent product memory

Your entire product — tech stack, architecture decisions, open questions, and past debates — lives in one persistent memory. Every session picks up where the last one left off.

Product Memory
Auth strategy — decided Jan 14
DB schema v3 — updated Jan 16
API design — REST + GraphQL hybrid
Caching strategy — open question

Real-time team sessions

Multiple users in one session with live presence and AI acting like an actual teammate — not a chatbot.

MCP server export

Your spec becomes a queryable MCP server. Coding agents ask live questions instead of reading stale files.

Gap detection

AI spots missing edge cases, undefined failure states, and architectural blind spots before they reach production.

Cross-session tracking

Past decisions stay queryable across sessions. Contradictions get flagged before the team wastes another sprint.

Auto diagrams

Discuss an auth flow or schema and instantly generate Mermaid diagrams that stay synced with the conversation.

What You Get

A 20-minute discussion
becomes a deployable spec.

Not another document that rots. A structured, queryable spec with every decision tracked, every open question flagged, and every schema ready for your coding agent.

Decisions with context and rationale
Database schemas extracted from discussion
Open questions assigned to owners
Constraints and edge cases flagged by AI
Ready for MCP export or markdown download
auth-spec.md — auto-generated
# Authentication Spec
Generated from 3 sessions · 12 decisions · 2 open questions
## Strategy
JWT with rotating refresh tokens
Access token TTL: 15 minutes
Web: httpOnly cookies, SameSite=Strict
Mobile: Keychain (iOS), Keystore (Android)
## Schema
sessions: id, user_id, token_hash, expires_at, device
refresh_tokens: id, session_id, token_hash, rotated_at
## Open Questions
○Rate limiting for token refresh — @alex to decide
○Session revocation: immediate vs lazy? — needs discussion

Before & After

The difference
context makes.

Without Contexire
2-hour Slack debate. Decision buried by Tuesday.
Dev codes from vague memory of what was discussed.
AI agent gets 3 sentences of context and ships the wrong thing.
Spec was outdated before the sprint started.
Next sprint opens by re-debating the same questions.
With Contexire
Same discussion happens inside Contexire with AI present.
AI extracts every decision into a structured, versioned spec.
Dev exports via MCP — agent knows auth, schema, constraints, and why.
Spec stays current as the conversation evolves.
Team ships what was actually decided. First time.

Who It's For

Built for people who ship.

Solo Builders

“I have 10 ideas and zero documentation.”

A thinking partner that remembers everything, pushes back when needed, and writes the specs you never find time to write.

Small Teams (2-8)

“Our decisions live in someone's head.”

A shared product brain. Decisions stop depending on memory, screenshots, and old Slack threads.

AI-First Builders

“I spend half my time writing context prompts.”

The layer between product decisions and your coding agent. Think once, capture it, export, and ship.

Why Now

The timing is
not accidental.

AI coding agents just hit mainstream

Cursor, Claude Code, Copilot, Windsurf — every team now has an AI that writes code. But none of them know what your team actually decided to build.

The bottleneck shifted

It's no longer "can AI write code?" — it's "does AI know what to build?" Teams that feed their agents the best context ship the fastest.

Context is the new moat

As AI code generation gets commoditized, the competitive advantage moves to who can give their agents the richest, most structured product context.

Pricing

Free while we build
the future of specs.

Contexire is free during early access. Pro and Team plans are coming — early users will get priority pricing.

Early Access
Limited spots
$0
free forever for early users
Unlimited sessions and team members
AI with persistent product memory
Auto-generated specs and diagrams
Markdown export
MCP server export
Full session history
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FAQ

Questions.

Still curious? Reach out. We reply fast.

Stop shipping what you
think you decided.

Every team building with AI agents needs a context layer between decisions and code. Start capturing yours.

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Or join the waitlist for updates

Contexire
contexire
Discuss. Spec. Ship.
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