Cursor IDE — Adding Persistent Memory and Skill Injection

Cursor is an excellent IDE. Its AI integration is fast, its tab completion is good, and its codebase indexing is solid. But it has the same memory problem as every other AI coding tool: each session starts from zero.

You close Cursor at midnight after a productive session. You open it the next morning. Cursor does not remember what you decided last night. It does not remember which approach you are using, which patterns are standard in your codebase, or which bugs you have already fixed. You have to rebuild that context every time.

What Cursor Offers Natively

Cursor has a few mechanisms that partially address context:

.cursorrules — a file in your project root that Cursor reads at session start. Good for high-level coding standards. Not designed to capture decisions made during development sessions. Requires manual maintenance.

Codebase indexing — Cursor indexes your codebase and uses it for retrieval. This is useful for code navigation and completion. It does not capture architectural intent, historical decisions, or the reasoning behind patterns.

Chat history — Cursor keeps a local history of AI conversations. You can reference previous chats manually. But there is no automatic injection of relevant historical context into the current session.

These are useful features. They are not a memory layer.

The Real Cost of Starting from Zero

Here is a realistic scenario for a two-week project:

Week one. You establish your data access pattern, decide against server actions in favour of tRPC, agree on a naming convention for database schemas, and discover a bug in how Next.js handles auth redirects on Vercel. These are all important decisions and learnings.

Week two. New session. Cursor suggests a server action for a form. You correct it. It suggests Prisma when you are using Drizzle. You correct it. It writes auth code that triggers the redirect bug you already fixed. You fix it again.

None of this is Cursor's fault. It does not know what happened in week one. The problem is the missing memory layer.

The Skill Problem

Beyond memory, Cursor (like all AI coding tools) has another limitation: generic knowledge. It knows how to write code generally. It does not automatically apply the best practices from Stripe's own engineers when you are integrating payments. It does not inject Cloudflare-specific patterns when you are writing a Worker. It does not know which testing approach works best for your specific stack.

Expert knowledge exists. It just does not inject automatically.

This is the skill injection problem. You can solve it by writing detailed prompts every time — or you can build a layer that scores your task and injects the relevant expertise before Cursor ever sees your request.

How SkillGod Adds Both to Cursor

SkillGod connects to Cursor via MCP (Model Context Protocol), which Cursor supports natively. Once connected, SkillGod runs two processes silently before every Cursor AI request:

Memory injection — SkillGod's memory layer captures decisions, patterns, and errors as you work. Before each Cursor request, it scores your current task against stored memories and injects the relevant ones. Your Drizzle decision, your tRPC pattern, your auth fix — all inject automatically without you doing anything.

Skill injection — 1,944 curated skills are scored against your current task in under 15ms. The top 3 matches inject before Cursor sees your prompt. Integrating Stripe? Stripe payment skills inject. Writing a Cloudflare Worker? CF-specific patterns inject. Zero manual effort.

SkillGod stores everything locally. A SQLite database at ~/.skillgod/. Nothing leaves your machine.

Setup for Cursor

Install SkillGod and connect it as an MCP server in Cursor's settings:

After install, SkillGod starts a local MCP server on port 3333. Add it to your Cursor MCP config:

That is the full setup. Memory captures automatically from your first session. Skills inject before every request.

What Changes After Setup

Day one after install: Cursor still starts fresh. SkillGod has no memories yet. But skills inject on the first session.

After a week: Cursor starts every session with your project context already loaded. The decisions from last Tuesday inject. The pattern you established on Monday injects. You stop re-explaining your project.

After a month: SkillGod has a substantial memory of your project. New team members onboard faster because SkillGod captures and injects institutional knowledge automatically.