You will get Custom MCP Server | Connect AI to your CRM, Database & Tools
Rising Talent
Rising Talent
Project details
MCP is how modern AI reaches your real systems. I will build a custom Model Context Protocol server that connects Claude, ChatGPT, Cursor, or your own agents to your CRM, database, and internal tools, securely.
What you get:
-A custom MCP server exposing exactly the tools and data your AI should reach
-Integrations: PostgreSQL, Salesforce, HubSpot, Notion, Slack, internal APIs, or anything with an API
-Authentication, RBAC, and audit logging built in from day one
-Clear tool schema so the model calls the right thing the right way
-Deployment: local, Docker, or cloud, with docs your team can extend
-Works with Claude Desktop, ChatGPT, Cursor, LangGraph agents, and custom clients
I build MCP servers as a senior full stack AI engineer who also builds the platforms around them, so your get security and reliability, not just a working prototype.
Message me with the systems your want your AI to reach, and I will map out the tools, the auth model, and a timeline before we start.
What you get:
-A custom MCP server exposing exactly the tools and data your AI should reach
-Integrations: PostgreSQL, Salesforce, HubSpot, Notion, Slack, internal APIs, or anything with an API
-Authentication, RBAC, and audit logging built in from day one
-Clear tool schema so the model calls the right thing the right way
-Deployment: local, Docker, or cloud, with docs your team can extend
-Works with Claude Desktop, ChatGPT, Cursor, LangGraph agents, and custom clients
I build MCP servers as a senior full stack AI engineer who also builds the platforms around them, so your get security and reliability, not just a working prototype.
Message me with the systems your want your AI to reach, and I will map out the tools, the auth model, and a timeline before we start.
AI Algorithms
Convolutional Neural Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Transformer Model, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AIOps, Conversational AI, Image Analysis, Image Recognition, Natural Language Generation, Object Detection, Text RecognitionAI Development Language
PythonAI Models
BERT, BLOOM, ChatGPT, Dolly, GPT-3, GPT-4, LLaMA, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$400
|
Standard
$950
|
Advanced
$2,400
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Batch Normalization | |||
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | |||
Model Deployment | |||
Model Documentation | - | ||
Model Monitoring | - | ||
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | - | - | |
NLP Tokenization | - | - | |
Pre-Training | - | - | |
Prompt Engineering | - | - | |
Setup File | - | - | |
Source Code | - | - |
About Michael
Full-Stack AI Engineer | AI SaaS, LLM, Python, LangChain, MCP Servers
Vancouver, United States - 9:52 pm local time
I've spent the last 8+ years as a Senior Full-Stack AI Engineer in enterprise SaaS, on products where “it mostly works” was never an acceptable answer. Now I bring that same discipline to your AI SaaS products: the platform, the product, and the AI core, built end to end by one person who's done it at scale.
𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃
• AI SaaS products, end to end - multi-tenant platforms with authentication, billing, dashboards, and the AI core designed in, not bolted on
• AI agents and multi-agent systems - LangGraph-based agents with the parts most builds skip: evaluation suites, monitoring, cost controls, and guardrails
• LLM applications and AI integration - OpenAI, Claude, and Gemini embedded in your product with structured outputs, function calling, and production-grade reliability
• RAG and knowledge systems - retrieval pipelines over your data with hybrid search, reranking, and measurable answer quality
• MCP servers and integrations - connecting AI to your CRM, databases, and internal tools through the Model Context Protocol
• Production operations - MLOps and LLMOps (evaluation pipelines, tracing, model and cost monitoring), DevOps (containerized deployments, CI/CD), and SecOps (authentication and RBAC, secrets management, audit logging)
𝐇𝐎𝐖 𝐘𝐎𝐔𝐑 𝐏𝐑𝐎𝐃𝐔𝐂𝐓 𝐆𝐄𝐓𝐒 𝐁𝐔𝐈𝐋𝐓
Scoping call - written architecture proposal - working prototype in weeks, not months - production hardening (evals, observability, security, cost) - documented handoff. You own the code. No vendor lock-in, no black boxes, and your team can maintain what I leave behind.
𝐓𝐄𝐂𝐇 𝐒𝐓𝐀𝐂𝐊𝐒
• Backend: Python, FastAPI, Node.js, PostgreSQL, Redis, Stripe
• Frontend: Next.js, React, TypeScript, Tailwind CSS, Vue.JS
• AI / LLM: OpenAI (GPT-4o and o-series), Anthropic Claude, Gemini, LangChain, LangGraph, LangSmith, MCP
• Retrieval: Pinecone, Qdrant, Weaviate, pgvector
• DevOps & Cloud: AWS, GCP, Docker, Kubernetes, CI/CD
• MLOps / LLMOps: LangSmith tracing, evaluation pipelines, model and cost monitoring
• SecOps: authentication and RBAC, secrets management, audit logging, security-first code review
𝐈𝐍𝐃𝐔𝐒𝐓𝐑𝐈𝐄𝐒
B2B SaaS, Marketing, fintech and financial services, healthcare, legal and professional services - environments where reliability, security, and compliance are not optional.
𝐖𝐇𝐘 𝐂𝐋𝐈𝐄𝐍𝐓𝐒 𝐇𝐈𝐑𝐄 𝐌𝐄
Most engineers are strong on the AI layer or the product layer. I've spent my career on both: the same person who designs your retrieval pipeline can build the dashboard, wire the billing, and get it deployed, then keep it observable, secure, and affordable in production. That's the difference between shipping a demo and shipping a product.
Send me a short message: what your product does (or will do), what stage it's at, and what's blocking you. I'll reply with an honest read and a concrete next step.
Steps for completing your project
After purchasing the project, send requirements so Michael can start the project.
Delivery time starts when Michael receives requirements from you.
Michael works on your project following the steps below.
Revisions may occur after the delivery date.
Define tool schemas, scopes, and the authentication model.
Build and test the MCP server against your systems.