Save common patterns as Boosters.
Save structured context and have it recalled automatically before starting any task. Keep them for yourself, share them with your team, or publish them to the community.
Works with
⚡
Claude Code
◎
Cursor
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Any MCP Client
Quick Start
{
"mcpServers": {
"ai-boost": {
"url": "https://mcp.ai-boost.io/mcp",
"transport": "streamable-http"
}
}
}.cursor/mcp.json, then authenticate with GitHub on first use.Saving to Your Library
It'll be recalled automatically next time it's relevant.
Extracting the reusable pattern from this conversation
Saving privately to My Library
Ready to recall automatically next time
The rules of expertise need to change in the age of AI
Experts are being asked to hand more and more of their knowledge to tools they do not control. We think that trust has to be earned, not assumed. These are not terms of service. They are commitments from one developer to another.
Your context is yours. Forever.
Private boosters are never indexed, sold, surfaced to others, or used to train any model. What you save stays entirely in your account.
Delete anything, any time.
You can remove any booster, any version, or your entire account at any point. Deletion is permanent and immediate. There is no archive.
Transparent internal process.
Pricing changes, policy updates, and platform decisions are announced in advance. We will not change the rules without giving you time to act.
The em-dash
We believe the em-dash is a valid — and useful — punctuation mark, and we will continue to use it regardless of what anyone else says.
Your expertise. Captured once. Available everywhere.
Private boosters are yours alone. Capture your expertise from any session. AI Boost embeds it for instant retrieval. Your agent surfaces it the moment context matches.
01
Capture any expertise
Tell your agent what you want to save. It reads your current context, proposes metadata, and creates a private booster in seconds.
02
Indexed and embedded
AI Boost processes the booster for keyword and semantic search so it can be retrieved accurately across all your future sessions.
03
Suggested automatically
When you start a task that matches a saved pattern, your agent surfaces the booster before it begins. You approve, it injects.
Save once, available for every future session
Tell your agent what to save. It handles the rest — including reminding you next time.
Save our custom auth middleware pattern as a private booster
Let me read the current auth middleware file to extract the pattern.
Ran Read file in filesystem
Got it. Based on the file, here are my suggested booster details:
Name: Custom Auth Middleware Pattern
Description: JWT validation, role-based guards, request context injection
Tags:
Visibility will be set to private. Confirm to save, or let me know what to change.
| Name | Custom Auth Middleware Pattern |
| Description | JWT validation, role-based guards, and request context injection for Express services |
| Tags | auth middleware jwt express typescript |
| Version | 1.0.0 |
| Visibility | Private |
| Price | 0 credits (personal use) |
Confirmed
Ran create_booster in ai-boost
| Booster ID | a3f2c901-7b44-4d1e-bc82-19e047f6a312 |
| Slug | custom-auth-middleware-pattern |
| Status | Saved to your library |
Your Custom Auth Middleware Pattern booster has been saved to your private library under custom-auth-middleware-pattern. It is only visible to you and will be suggested automatically in future sessions.
Add protected routes to the new payments service
Before I start, let me check if there are any relevant boosters in your library.
Ran search_boosters in ai-boost
Found in your library
Custom Auth Middleware Pattern
I found your saved auth middleware booster. Would you like me to inject it before I begin?
Yes, inject it
Ran get_booster in ai-boost
Booster injected into context
Your auth middleware conventions are loaded. I will follow your JWT validation and role-based guard patterns throughout this task.
Every session starts blank
Memory systems capture history, but they cannot curate it. The expertise your agent needs (your conventions, your gotchas, lessons that took years to learn) has nowhere to live between sessions.
Every session starts from scratch
Patterns you use every day — your auth flow, your infra conventions, your API design rules — live in human memory. Your agent has no access to them.
Memory is not curation
Memory plugins record everything, which means they retrieve everything. The signal-to-noise ratio makes them unreliable for injecting the specific, structured knowledge your agent actually needs.
No way to share structured expertise
Domain experts have invaluable knowledge. There is currently no mechanism to package, distribute, and inject that expertise into an LLM at the moment it is needed.
How a booster works
01
Save
Tell your agent about a convention, pattern, or workflow. AI Boost packages it as a booster and indexes it using keywords and semantic embeddings.
Private by default; publish when you are ready02
Suggest
On your next session, your agent queries AI Boost automatically before starting a task. If a relevant booster exists (yours or from the community) it is surfaced for your approval.
Proactive, not passive03
Inject
You approve. The full context payload flows directly into the agent's context window. Conventions, patterns, examples: available immediately. No copy-paste, no setup.
Re-injectable at any point in a sessionConnect in minutes
AI Boost is an MCP server. Add it to your agent client once and it will be available across every project automatically.
Open your Cursor MCP config
Create or edit .cursor/mcp.json in your home directory or project root.
Add the AI Boost server entry
{
"mcpServers": {
"ai-boost": {
"url": "https://mcp.ai-boost.io/mcp",
"transport": "streamable-http"
}
}
}Authenticate with GitHub OAuth
On first use Cursor will open a browser tab. Sign in with GitHub, grant access, and you will be redirected back automatically.
Top up credits and start using boosters
Visit app.ai-boost.io/billing to add credits, then ask Cursor to search for a booster relevant to your task.
Watch the full flow
Three messages to go live
Just tell the agent what you want to publish. It handles the rest.
I would like to publish this as a free public booster
I'll help you publish this as a free public booster. Visibility and price are already set — public means listed in the marketplace; your GitHub repo can stay private.
One question before I proceed:
Link to a GitHub repository
Let me look up the repo to auto-suggest metadata.
Ran Lookup GitHub Repo in ai-boost
Based on the GitHub repo, here are my suggestions — let me know if you'd like to change any of them:
Name: Stripe Payment Integration Guide
Description: A quick-setup guide for Stripe payments
Version: 1.0.0 (no releases found, defaulting)
Branch:
mainTags:
Visibility is public, price is 0 credits — both confirmed from your message. One last question:
Whole repository
Here's a full summary of the booster submission — please confirm before I proceed:
| Name | Stripe Payment Integration Guide |
| Description | A quick-setup guide for Stripe payments |
| Tags | stripe payments python webhook subscription billing |
| Version | 1.0.0 |
| Branch | main |
| Repo URL | github.com/AI-Boost-IO/stripe-payment-integration-guide |
| Delivery | Whole repository |
| Visibility | Public (marketplace listing) |
| Price | 0 credits (free) — pre-confirmed |
Does everything look correct? Reply "confirmed" to submit, or let me know what to change.
Confirmed
Ran Submit Booster From Repo in ai-boost
The booster was submitted and approved. Here's the summary:
| Booster ID | fd904501-cda7-4a9f-aca9-34f539b5fc5a |
| Version ID | ff6135a2-0432-4bca-8fc1-232c9f05d0d5 |
| Slug | stripe-payment-integration-guide |
| Status | Approved |
The Stripe Payment Integration Guide booster is now live on the AI Boost Marketplace and discoverable under the slug stripe-payment-integration-guide.
Expert human experience is hard to find in the age of AI
LLMs cannot learn from what they have never seen. Your hard-won patterns are exactly what other developers need. Make your private boosters public when you are ready. They surface automatically in every relevant session across the community.
Developers are increasingly surrounded by AI-generated knowledge. Boosters backed by real human experience are a different category entirely. When you share one, you are contributing something the models genuinely cannot replicate.
What sharing looks like
01
Your private booster already exists in your library. You just flip the visibility to public.
02
It goes through automated LLM adversarial review and human approval to ensure quality.
03
It becomes searchable across the community. Any developer whose agent matches it can inject it.
04
You earn AI Boost credits for every injection of your booster — a direct measure of your contribution to the community.
What the community is using
Django on AWS EC2 with Terraform
A setup guide for deploying a Dockerised Django app on AWS EC2 using Terraform-managed infrastructure (VPC, EC2, S3, IAM, EIP).
Django Channels + Celery + Next.js + Terraform/AWS
Full-stack skeleton documenting the canonical patterns for a monorepo SaaS backend: Django 5.2 + Strawberry GraphQL + Django Channels 4 + Celery + Next.js 16 + Material UI v9 + Apollo Client 4 + Terraform on AWS EC2. Covers ASGI routing, WebSocket subscriptions with Redis pub/sub, Celery workers and Beat scheduler, Next.js App Router with RSC and Client Components, MUI v9 theming, GraphQL codegen, Docker Compose dev/prod split, and Vercel deployment for the frontend.
Stripe Payment Integration Guide
A quick-setup guide for Stripe payments
Next.js SEO Configuration
Production-grade SEO configuration patterns for a Next.js 16 App Router site — metadata API, Open Graph, Twitter Card, i18n copy separation, dual-domain routing, semantic HTML, GTM/GA4 analytics, and robots/sitemap generation.
Next.js + MUI Typography Guide
Font setup guide for Next.js + MUI projects. Covers Inter Variable for body and headings (weight 510 for h1/h2), IBM Plex Mono for code elements, next/font/google loading, MUI theme configuration, and rationale for each decision.
Crypto Wallets — Secure Multi-Chain Wallet Engineering
Production-grade reference for building bulletproof crypto wallets: BIP32/39/44/84 key derivation, transaction building & validation, fee estimation, multi-chain support (BTC/EVM/Solana/Cosmos/Tron/XRP), React Native/Expo patterns, and a non-negotiable fund-loss prevention ruleset. Distilled from production wallets (OneKey, MetaMask, BlueWallet). Inject when writing or reviewing wallet code so every key/address/amount/transaction path is verified before touching real funds.
NextJS Monorepo with Bun and Biome
A lightweight monorepo pattern for two independent Next.js 15 apps (public marketing site and authenticated dashboard) managed with Bun, linted and formatted with Biome, and deployed to separate Vercel projects from the same git repository.
Built for serious agent workflows
Every design decision optimises for two things: the agent gets the right context instantly, and the user stays in control.
Proactive Discovery
Your agent calls the marketplace autonomously before starting any implementation task. No prompting required — it just works, like a reflex.
Semantic + Keyword Search
Boosters are ranked by relevance using embeddings and full-text search. The right booster surfaces based on what your agent is actually trying to do.
Review Pipeline + Signing
Every booster passes automated LLM adversarial review and human approval before going live. Cryptographic signing ensures content integrity at inject time.
Open Knowledge Commons
Share your expertise with the community. Your boosters surface proactively in relevant sessions across every member's workspace — knowledge that compounds over time.
Versioning & Model Tags
Every booster is semantically versioned. Model compatibility tags tell you which LLMs the creator tested against. Pin to a version for reproducible results.
Your library.
Your community.
Your call.
Private boosters are only ever visible to you. When you decide to share, they become available to the whole community, and you earn credits for every injection.
You have knowledge that took years to accumulate. AI Boost lets you package it as a structured context booster without any ongoing effort on your part.
Your library is private by default — share individual boosters on your own terms
Submit any structured knowledge: conventions, patterns, guides, annotated snippets
Automated LLM review and human approval keeps quality high and fraud low
Version your boosters freely; diff-focused review makes updates fast
Your booster surfaces proactively in every relevant agent session across the community
Earn credits every time a developer injects your booster — per-injection, ongoing
Your booster becomes part of a growing knowledge commons used by developers worldwide