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MCP server · RAG

AIForge

Unified registry & router for agent skills, MCP servers, and Claude Code plugins.

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Scored 29 days ago · breakdown

About AIForge

AIForge is an MCP server in the RAG category: unified registry & router for agent skills, MCP servers, and Claude Code plugins.

The repository has 2 stars and 0 forks.

Install

From source
git clone https://github.com/psypherai/AIForge

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (5)

DockerLatest

Parameters not published.

Node.js>= 22

Parameters not published.

Python>= 3.12

Parameters not published.

pnpm>= 10

Parameters not published.

uvLatest

Parameters not published.

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README

AIForge Starter Pack

The #1 AI-native monorepo template for 2026+

Ship web, mobile, and AI products at maximum velocity with 90%+ code sharing.

GitHub stars GitHub forks PRs Welcome

Next.js React Expo FastAPI Turborepo Supabase pnpm Tailwind CSS

Getting Started · AI Quick-Start · Why AIForge · Deploy · Contributing · Psypher AI


Love this project? Give it a :star: to help others discover it!

What is AIForge?

AIForge is the canonical monorepo blueprint for every AI product you build in 2026 and beyond. One pnpm dev command spins up a Next.js web app, an Expo mobile app, and a FastAPI + LangGraph backend — all sharing 90%+ of their code.

# Scaffold → Install → Run (under 2 minutes)
npx degit psypherai/AIForge my-app && cd my-app
pnpm install && cp .env.example .env
pnpm dev

Web on localhost:3000 · Mobile on localhost:8081 · API on localhost:8000 · Docs on localhost:8000/docs


Why AIForge?


Tech Stack (February 2026 — Best-of-the-Best)

Layer Technology Why
Monorepo Turborepo v2.8 (Rust core) Remote cache, sub-second builds
Package Manager pnpm v10 workspaces Fast, strict, disk-efficient
Web Next.js 16 + React 19.2 + Turbopack RSC, streaming, React Compiler
Mobile Expo SDK 54 + React Native + Solito Universal navigation, OTA updates
Styling NativeWind + Tailwind CSS + shadcn/ui One styling system everywhere
AI (TypeScript) Vercel AI SDK + LangGraph.js + Zod Streaming, tools, structured outputs
AI (Python) FastAPI + LangGraph + LangChain Production agentic loops
Multi-Agent Supervisor, Pipeline, Parallel, Debate 4 orchestration patterns out of the box
MCP @modelcontextprotocol/sdk Expose app capabilities to any AI model
RAG Supabase pgvector + OpenAI embeddings Vector search in your database
Realtime AI Supabase Realtime + AI streaming Collaborative AI with live presence
Edge Functions Supabase Edge (Deno) Serverless AI at the edge
API Client @hey-api/openapi-ts + TanStack Query v5 Auto-generated, type-safe
Auth/DB Supabase (auth + Postgres + realtime) All-in-one BaaS
Observability Langfuse + LangSmith Trace every AI call, open-source
PWA Service Worker + Web Manifest Installable web app with offline support
CLI create-aiforge npx create-aiforge my-app scaffolding
Tooling Biome + Vitest + Playwright 100x faster linting, full testing

Architecture

.
├── apps/
│   ├── web/                 # Next.js 16 + Turbopack + shadcn/ui + PWA
│   ├── mobile/              # Expo SDK 54 + Solito + NativeWind
│   └── backend/             # Python FastAPI + LangGraph + uv
│
├── packages/
│   ├── ui/                  # Shared UI (shadcn + Tailwind RN primitives)
│   ├── core/                # Types, Zod schemas, utils, constants
│   ├── ai/                  # Prompt factory, tools, RAG, multi-agent, realtime
│   ├── mcp/                 # MCP server + client (Model Context Protocol)
│   ├── api-client/          # Generated OpenAPI client + React Query hooks
│   ├── config/              # Shared Tailwind, TypeScript configs
│   ├── observability/       # Langfuse + LangSmith wrappers
│   ├── db/                  # Supabase types + pgvector helpers
│   ├── evals/               # Agent evaluation suite
│   ├── create-aiforge/      # CLI scaffolding tool (npx create-aiforge)
│   └── eslint-config/       # ESLint flat config (fallback)
│
├── supabase/
│   └── functions/           # Edge Functions (ai-chat, embed, webhook)
│
├── docs/                    # Upgrade guides and documentation
├── turbo.json               # Turborepo config (incl. Python tasks)
├── docker-compose.yml       # Local Supabase + Langfuse + Backend
└── .github/workflows/       # CI: TS + Python + E2E + Docker

Getting Started

Prerequisites

Tool Version Install
Node.js >= 22 nodejs.org
pnpm >= 10 npm install -g pnpm
Python >= 3.12 python.org
uv Latest curl -LsSf https://astral.sh/uv/install.sh | sh
Docker Latest docker.com

Quick Start

# 1. Scaffold and install
npx degit psypherai/AIForge my-app
cd my-app
pnpm install

# 2. Set up Python backend
cd apps/backend && uv sync && cd ../..

# 3. Configure environment
cp .env.example .env
# Edit .env with your API keys (OPENAI_API_KEY, SUPABASE_URL, etc.)

# 4. Start local services (optional — for Supabase + Langfuse)
docker compose up -d

# 5. Run everything concurrently
pnpm dev

That's it. Three apps running simultaneously:

Service URL Stack
Web localhost:3000 Next.js + Turbopack
Mobile Web localhost:8081 Expo + NativeWind
Backend API localhost:8000 FastAPI + Uvicorn
API Docs localhost:8000/docs Scalar API Reference
Supabase Studio localhost:54323 Postgres + pgvector
Langfuse localhost:3100 AI Observability

Commands

pnpm dev              # Start all (web + mobile + backend)
pnpm dev:web          # Next.js only
pnpm dev:mobile       # Expo only
pnpm dev:backend      # FastAPI only
pnpm build            # Build all packages
pnpm test             # Run all tests (Vitest)
pnpm typecheck        # TypeScript check
pnpm check            # Biome lint + format
pnpm api:generate     # Regenerate API client from OpenAPI spec

AI Quick-Start Guide

1. Streaming Chat (Web)

The /chat page is pre-built with Vercel AI SDK:

// apps/web/app/api/chat/route.ts — already set up!
import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
import { SYSTEM_PROMPTS } from '@aiforge/ai/prompts';

export async function POST(req: Request) {
  const { messages } = await req.json();
  const result = streamText({
    model: openai('gpt-4o'),
    system: SYSTEM_PROMPTS.assistant,
    messages,
  });
  return result.toDataStreamResponse();
}

2. Universal AI Hook (Web + Mobile)

import { useAI } from '@aiforge/ai/use-ai';

function ChatScreen() {
  const { messages, send, isLoading } = useAI({
    model: 'gpt-4o',
    systemPrompt: 'You are a helpful assistant.',
  });

  return (
    <View className="flex-1 p-4">
      {messages.map(m => <Text key={m.id}>{m.content}</Text>)}
      <Button onPress={() => send('Hello!')} disabled={isLoading}>Send</Button>
    </View>
  );
}

3. Structured Outputs

import { openai } from '@ai-sdk/openai';
import { generateObject } from 'ai';
import { extractionSchema } from '@aiforge/ai/schemas';

const { object } = await generateObject({
  model: openai('gpt-4o'),
  schema: extractionSchema,
  prompt: 'Extract entities: "Tim Cook announced iPhone 17 in Cupertino"',
});
// object.entities → [{ text: 'Tim Cook', type: 'person' }, ...]

4. Tool Calling

import { createToolSet } from '@aiforge/ai/tools';
import { generateText } from 'ai';

const { text } = await generateText({
  model: openai('gpt-4o'),
  tools: createToolSet(['search', 'calculator', 'datetime']),
  prompt: 'What time is it in Tokyo?',
  maxSteps: 5,
});

5. RAG with pgvector

import { searchSimilar, upsertDocuments } from '@aiforge/ai/rag-helpers';

// Index documents
await upsertDocuments(supabase, [
  { content: 'AIForge is the best monorepo.', metadata: { source: 'docs' } },
]);

// Semantic search
const results = await searchSimilar(supabase, 'best monorepo', { topK: 5 });

6. LangGraph Agent (Python)

curl -X POST http://localhost:8000/api/v1/chat \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "Hello!"}]}'

7. Agent Evaluations

import { runEval, scorers, EXAMPLE_DATASET } from '@aiforge/evals';

const results = await runEval({
  dataset: EXAMPLE_DATASET,
  agent: myAgent,
  scorers: [scorers.relevance, scorers.coherence, scorers.safety],
});
console.log(`Average score: ${results.summary.averageScore}`);

Deployment

Web (Vercel)

vercel --cwd apps/web

Mobile (Expo EAS)

cd apps/mobile && eas build --platform all && eas submit --platform all

Backend (Fly.io / Render / Railway)

cd apps/backend && fly launch && fly deploy

Full Stack (Docker Compose)

docker compose up -d

Roadmap

  • Monorepo with Turborepo + pnpm
  • Next.js 16 web app with shadcn/ui
  • Expo mobile app with NativeWind
  • FastAPI + LangGraph backend
  • Supabase pgvector RAG
  • Langfuse observability
  • Agent evaluation suite
  • Docker Compose for local dev
  • GitHub Actions CI
  • MCP (Model Context Protocol) server + client
  • Multi-agent orchestration (Supervisor, Pipeline, Parallel, Debate)
  • Supabase Edge Functions (ai-chat, embed, webhook)
  • Real-time collaborative AI (Supabase Realtime)
  • PWA support (installable web app + offline)
  • Quick scaffold via npx degit psypherai/AIForge
  • Expo SDK 55 + NativeWind v5 upgrade guide
  • Scalar API Reference (replaced Swagger UI)

Coming Next

High Priority — Differentiators

  • A2A Protocol (Google Agent-to-Agent) — agent-to-agent communication alongside MCP
  • Voice AI — useVoiceChat hook with OpenAI Realtime API / Deepgram STT+TTS
  • AI Guardrails — content filtering, PII detection, prompt injection protection
  • Human-in-the-Loop — AI actions requiring user approval before execution
  • AI Payments (x402) — agents that can pay for tools and services

Medium Priority — Production Essentials

  • AI Background Agents — long-running async tasks with notifications
  • CLI scaffolding tool (npx create-aiforge) — interactive project setup
  • Multi-provider LLM Router — auto-route between OpenAI / Anthropic / Gemini / local models
  • Fine-tuning Pipeline — scripts to fine-tune on your app's data
  • Prompt Playground — built-in UI to test and iterate prompts
  • E2E AI Testing — automated LLM output validation beyond unit tests

Ecosystem Integrations

  • Cloudflare Workers AI — alternative edge deployment
  • Expo Push Notifications + AI — push triggered by AI agents
  • Stripe Integration — SaaS billing with AI usage metering
  • Admin Dashboard — analytics for AI usage, costs, latency

Contributing

We love contributions! Check out our Contributing Guide for details on how to get started.

Whether it's a bug fix, new feature, documentation improvement, or even a typo fix — every contribution is valued.


Community


Star History


License

MIT — Psypher AI 2026


Built with purpose by Psypher AI

If AIForge helped you ship faster, consider giving it a :star:

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README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About AIForge

How do I install AIForge?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is AIForge safe to use with an AI agent?

Its trust score is 35 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is AIForge still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.