Autonomous AI Systems · Est. 2024 · Bareilly, India

ANUJ

Building Intelligence, Elegantly

Multi-Agent Orchestration · 21 MCP Servers · Zero Cloud Cost
Local-first AI infrastructure that operates at the edge of possibility
Available for exclusive AI engagements worldwide

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21 MCP Servers
11 LLM Providers
$0 Monthly Cloud Cost
Agent Scale
Solo Architect
Multi-Agent Orchestration
21 MCP Servers
Zero Cloud Cost
Local-First Architecture
Semantic Memory
LangGraph & CrewAI
Autonomous OSINT
ChromaDB Vector Memory
11 Free LLM Providers
AI Freelance Worldwide
Multi-Agent Orchestration
21 MCP Servers
Zero Cloud Cost
Local-First Architecture
Semantic Memory
LangGraph & CrewAI
Autonomous OSINT
ChromaDB Vector Memory
11 Free LLM Providers
AI Freelance Worldwide
A
21 MCP Servers
11 LLM APIs
Possibilities
$0 Cloud Cost
Bareilly, Uttar Pradesh · India

The mind
behind M4ST

I am Anuj — a solo AI systems architect operating from Bareilly, India. I build autonomous, multi-agent AI infrastructures that think independently, collaborate across workflows, and execute without human hand-holding.

My philosophy is radical: maximum capability at zero recurring cost. The M4ST stack runs 21 MCP servers across 11 free LLM providers with ChromaDB-powered semantic memory — entirely local-first, entirely offline-capable.

I am available for exclusive AI engineering engagements — from architectural consulting to full-scale autonomous pipeline builds. If you need AI that genuinely works without a cloud bill, you've found the right architect.

"Intelligence should be autonomous, not dependent — local, not leased."

— Anuj, M4ST Architect

The future of AI is not the cloud.
It is the edge.

On the M4ST Approach · 2024

01

Local-First, Always

Every agent, every tool, every memory layer runs on your hardware. No API calls to proprietary clouds, no data leaving your perimeter, no monthly bill for intelligence.

02

Zero-Cost Infrastructure

I route across 11 free LLM providers intelligently — quality-aware, cost-zero, fallback-resilient. The M4ST stack proves enterprise-grade AI needs no enterprise-grade budget.

03

Genuine Autonomy

My agents don't ask for permission. They decompose complex tasks, collaborate across specialized sub-agents, build semantic memory, and deliver results — independently.

04

Composable Architecture

21 MCP servers, each precision-built for a specific domain — file systems, web intelligence, code execution, memory, API bridges. Swap, extend, compose infinitely.

Work crafted
with precision

Every project in the M4ST portfolio represents a genuine technical challenge solved with elegant architecture. These are not demos or toys — they are production systems that run autonomously, scale locally, and cost nothing to operate.

01

Multi-Agent Orchestration

M4ST Agent Orchestration Stack

The flagship system. A local-first multi-agent orchestration layer built on LangGraph and CrewAI, coordinating specialized agents across 21 MCP servers with ChromaDB-powered semantic memory, intelligent LLM routing across 11 free providers, and autonomous task decomposition. Runs entirely offline with zero recurring cloud cost.

LangGraph CrewAI ChromaDB MCP Protocol Python Ollama
02

Intelligence Systems

Autonomous OSINT Intelligence Framework

A self-directed open-source intelligence gathering system. Agents autonomously identify, collect, cross-reference, and analyze multi-source data. Includes anomaly detection, pattern recognition across temporal data, and automated report generation — all without human intervention once tasked.

LangChain Autonomous Agents OSINT APIs Data Fusion
03

Memory Architecture

Semantic Memory Engine

Persistent vector-based memory with intelligent retrieval. Goes beyond naive RAG — implements semantic clustering, relevance decay, context-aware injection, and cross-session memory consolidation for agents that genuinely remember and learn across long operational periods.

ChromaDB Embeddings RAG Vector DB
04

Developer Tools

Smart GitHub Repository Manager

AI-powered repository intelligence layer. Automated documentation generation that understands code intent, smart PR analysis with architectural impact assessment, autonomous issue triage, dependency graph analysis, and security audit agents — deployed live at GitHub.com.

GitHub API MCP Code Analysis Automation
05

Infrastructure

21-Server MCP Ecosystem

A complete model context protocol server suite covering: file system operations, browser automation, web intelligence, code execution sandboxes, persistent memory, API bridges, database connectors, image analysis, and specialized domain tools. The operational backbone of the entire M4ST agent fleet.

MCP Protocol TypeScript Python FastAPI

What I offer

Multi-Agent System Architecture

Complete design and implementation of autonomous multi-agent systems. From requirements to production — specialized agents, orchestration logic, tool integration, and monitoring.

  • LangGraph / CrewAI orchestration
  • Specialized agent design
  • Inter-agent communication protocols
  • Task decomposition strategies
  • Production deployment & monitoring
🔗

MCP Server Development

Custom Model Context Protocol server development for any domain. File systems, APIs, databases, web intelligence, code execution — I build the tools your agents need.

  • Custom MCP server design
  • TypeScript & Python implementations
  • API bridge development
  • Database & storage connectors
  • Security & access control
🧠

AI Pipeline Automation

End-to-end automation of complex workflows using AI agents. Data processing, document analysis, research automation, code generation pipelines — autonomous and cost-zero.

  • Workflow analysis & automation design
  • Document processing pipelines
  • Research & data gathering automation
  • Report generation systems
  • Integration with existing systems
💎

LLM Orchestration & Routing

Intelligent multi-provider LLM routing systems. Quality-aware, cost-optimized, fallback-resilient inference across free and paid providers. Zero-cost production AI.

  • Multi-provider routing logic
  • Cost optimization strategies
  • Fallback & resilience design
  • Quality scoring systems
  • Ollama local inference setup

The process

01

Discovery

Deep analysis of your requirements, existing systems, and goals. I map every agent needed, every tool required, every data flow involved. Nothing is assumed.

02

Architecture

Precision system design. Agent hierarchy, MCP server selection, memory architecture, LLM routing logic, and integration points — blueprinted before a line is coded.

03

Build

Solo, focused development. I write clean, documented, production-ready code. Every agent tested in isolation, then end-to-end. No shortcuts, no technical debt.

04

Deploy & Hand-off

Full production deployment with documentation, monitoring setup, and knowledge transfer. You own the system completely — no vendor lock-in, no dependencies on my continued involvement.

The arsenal

Agent Frameworks

LangGraph
CrewAI
LangChain
AutoGen
Pydantic AI

Infrastructure & Memory

ChromaDB
MCP Protocol
Ollama
FastAPI
Docker

Languages & Tools

Python
TypeScript
JavaScript
Git & GitHub
Linux / CLI
"I believe the most powerful AI systems are not the most expensive ones — they are the most thoughtfully architected ones."

Anuj · M4ST · 2026

ENGAGE

Available for Work

Ready to
engage AI?

I take on a limited number of engagements each quarter.
Premium AI architecture, automation, and agent systems — worldwide.

✦ Send a Message ✦
Currently accepting new engagements · Worldwide