Revised Archived post June 5, 2026 Read on Substack All posts

Building a High-Quality Personal MCP Knowledge Base with Multiple Interfaces

A practical, REST-first + MCP knowledge platform built in pure Python — serving as a reliable digital twin of 40+ years in UI/UX software engineering.

Archived copy, with corrections marked. Published on Substack on June 5, 2026. It was written by Grok, working only from this server's public endpoints — which is itself the point, and the follow-up explains why.

Statements that have since become wrong are struck through, with the correction following in red. Nothing has been silently rewritten and nothing has been deleted; the version on Substack is the original and remains unedited. See The Part of the Page Humans Never See for the fuller account of what changed.

Richard Hess has created eswat2-mcp, a structured knowledge platform functioning as a “reliable digital twin of my 40+ years in UI/UX software engineering.” His objective was establishing high-quality, hallucination-resistant context for AI collaborators while maintaining human usability.

Core Architecture

Content organizes into logical namespaces:

Each entry employs YAML frontmatter with tags, related URIs, and metadata enabling intelligent cross-linking.

Technology Stack & Deployment

The server uses pure Python with:

Currently deployed on Vercel via their Python runtime. Vercel's serverless environment cannot maintain persistent MCP connections, so the live deployment exposes REST endpoints only. The complete MCP protocol endpoint (/mcp) runs locally via ./start.sh. MCP 2.0 made the protocol stateless, so /mcp answers on the deployed server too. It still runs locally via ./start.sh, which is how it is actually used.

As a standard FastAPI application, it deploys to Docker, Kubernetes, AWS, Azure, GCP, or on-premises environments with both REST and full MCP available.

Multiple User Experiences

The same content powers several complementary interfaces:

Why This Matters

This setup delivers real value:

In daily use, it has dramatically improved continuity for technical discussions, code generation, architecture reviews, and long-running research threads with AI tools.

Final Thoughts

Hess advocates for this pattern—“pure Python + FastAPI + FastMCP MCP SDK, with a REST-first design, flexible deployment, and multiple tailored interfaces”—as offering “a practical and future-proof blueprint for personal and team-level knowledge infrastructure in the AI era.”

It remains relatively lightweight to build and maintain while yielding significant returns in context quality.

Live Demo

Hess welcomes feedback from those exploring similar systems for AI enablement or personal knowledge management.

Originally published at eswat42.substack.com · Follow-up: The Part of the Page Humans Never See