How to Build an MCP Server From Scratch in 2026 (Zero Coding)

Item: How to Build an MCP Server From Scratch in 2026 (Zero Coding)
Rating: 3
Author: PostSingularity Institute

by Astro K Joseph · View the channel on PSI

Applied Sciences & Engineering AI — News & Applications UYComputer science UYQArtificial intelligence (AI)

🎙 Astro K Joseph 👥 85K 📅 September 19, 2026 ⏱ 28 min 👁 51 📄 tutorial 🧭 2026-09-19

Available in: English (current) Français

Keywords

MCPNo-codeDeploymentSuperbaseAI

Summary

This tutorial demonstrates building a Model Context Protocol (MCP) server from scratch without writing code, using AI and the MCP Use framework. The creator shows a demo of ‘Pocket Ledger’, a personal expense tracker MCP app, highlighting its integration with Claude and ChatGPT. The process involves creating a detailed prompt to be fed into Cursor with the Opus 5 model, which then scaffolds the server. Backend services include Superbase for authentication, database, and file storage, and OpenAI’s vision model for receipt analysis. Steps cover setting environment variables, running database migrations, configuring authentication providers, testing via the MCP inspector, and deploying on Manufact. The video also explains connecting a custom domain and redeploying. The entire build takes about 37 minutes, with deployment around 2 minutes. The tutorial emphasizes the ease of using AI to create functional MCP apps without manual coding, and provides a link to a reusable prompt template.

149 words

Critical Evaluation

Value of the Information & Strength of the Argument

The video provides a concrete, replicable workflow for building MCP servers with AI, illustrating the power of prompt engineering to generate backend code. The argument is supported by a live demonstration, showing the server working with real AI clients. It offers practical advice on configuration and deployment, making it valuable for developers seeking low-code solutions. However, the argumentation is subjective, based on the creator’s personal success, and lacks comparative analysis or independent validation.

Scientific Rigor, Source Quality, Title Accuracy

The video is a tutorial, not academic content. It cites the tools used (MCP Use, Manufact, Superbase, OpenAI) via links in the description, but provides no scientific references or external validation. The title is accurate and directly reflects the content, with no misleading elements. The practical nature of the tutorial makes sources appropriate for its purpose, but scientific rigor is limited.

149 words

Title / Content Match

The title accurately describes the content: a guide to building and deploying an MCP server without coding, using AI tools.

Quality & Reliability

6/10

The video offers a practical, step-by-step tutorial without formal citations or peer-reviewed references. It relies on the creator's personal experience and demonstrations, which is appropriate for a hands-on guide but limits scientific rigor.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

MCP Use GitHub Repository — Used as the framework for building the MCP app
Manufact - Build and Deploy MCP Apps — Platform for deploying the MCP server
Prompt Document (Google Docs) — Detailed prompt used to generate the MCP app with AI
aiholiq Newsletter — Promoted newsletter, not directly used in tutorial

External References

Contribution & Novelties

The tutorial offers a practical, no-code approach to building MCP servers, leveraging AI to generate full-stack applications. It demonstrates an integrated workflow combining MCP Use, Superbase, and Manufact, which is an original contribution for those seeking to quickly deploy MCP services. It also provides a reusable prompt template, enhancing reproducibility.

Pour aller plus loin :

Model Context Protocol (MCP) - Official Documentation — Core protocol underlying the tutorial; essential to understand MCP’s architecture.
Supabase Documentation — Used for authentication, database, and storage; key backend service in the video.
OpenAI Vision Guide — Explains the vision capability used for receipt analysis in the tutorial.
Anthropic Claude — One of the AI clients integrated with the MCP server.

116 words

Radar Profile

The profile shows balanced scores across quantity, quality, technical level, and reliability, indicating a well-rounded tutorial that offers substantial practical information with moderate technical depth and reliable steps, though not scientifically rigorous.

Reliability 6/10