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I will build a custom mcp server for your ai agents
Junaid A
About this gig
I will build a production-grade MCP (Model Context Protocol) server that gives your AI agents real tool access.
MCP is the new standard for connecting AI models (Claude, GPT, Gemini) to external services. Instead of fragile prompt engineering, MCP gives agents structured, reliable tool access to your APIs, databases, and business systems.
My MCP experience shipped and production:
- Tie-MCP: Unified MCP platform integrating 8 services (Metabase, Klaviyo, Shopify, GTM, etc.) on Google Cloud Run
- CineCommand: MCP execution layer translating Claude commands into Cinema 4D operations
- TWA News: MCP servers for AI-agent orchestration and content automation
What I build:
- Custom MCP tool servers for your specific business APIs
- Multi-service MCP platforms with shared auth, logging, and secret management
- MCP integration into existing AI agent workflows
- Containerized deployment (Docker, Cloud Run, AWS)
Tech: Python, FastAPI, TypeScript, Docker, GCP Cloud Run, AWS Lambda
Very few developers have production MCP experience. I have three shipped platforms.
Get to know Junaid A
Junaid A
I Build Production AI Systems: Agents, MCP Servers, Multi Tenant SaaS
- FromPakistan
- Member sinceAug 2020
- Avg. response time1 hour
- Last delivery3 years
Languages
Urdu, English
AI Solutions Architect & Full-Stack Engineer | Founder of Labverse
I build production AI systems — not demos. Specializing in autonomous AI agents, MCP servers, and enterprise SaaS platforms.
Shipped: Multi-tenant cybersecurity SaaS (AWS), AI-powered WhatsApp business agent (GPT-4/LangChain), unified MCP platform integrating 8 services (GCP), logistics ERP (Frappe/ERPNext), health-tech with AI insights, multilingual news automation.
Tech: Python, NestJS, Next.js, OpenAI/Claude/Gemini, LangChain, AWS, GCP, Stripe, Docker.
10+ years. 10+ production platforms. Let's build yours.
My Portfolio
FAQ
What is MCP (Model Context Protocol)?
MCP is an open standard (pioneered by Anthropic) that lets AI models interact with external tools in a structured way. Think of it as a USB port for AI — plug any service in, and the AI can use it reliably.
How is this different from just giving the AI an API key?
MCP provides structured tool definitions, input validation, error handling, and security layers. Raw API access is fragile and insecure. MCP is production-grade.
Can you integrate with [specific SaaS tool]?
If it has an API, I can build an MCP server for it. I've integrated Metabase, Klaviyo, Shopify, GTM, Stape, API7/APISIX, and Cinema 4D.
Do you only work with Claude?
No. MCP works with any model that supports tool use — Claude, GPT-4, Gemini, and open-source models.
Can this connect to my internal database?
Yes. I can build MCP tools that query your PostgreSQL, MongoDB, DynamoDB, or any database with proper access controls.
