Your AI Writes Better Code When It Knows Your Standards

I've been building something I'm really excited about and wanted to share it here: CodeContext.

The Problem

If you use AI coding assistants — Claude, Cursor, Windsurf, Copilot — you've probably noticed the same thing I did: they write decent code, but they don't know your rules. Your naming conventions, your error handling patterns, which libraries you prefer, how your API responses should be structured. You end up correcting the same things over and over.

CLAUDE.md files and rules files help, but they live in your repo, get stale, and don't scale across projects or teams.

What CodeContext Does

CodeContext is a knowledge base for your coding standards and API specs that delivers them directly to AI assistants via MCP (Model Context Protocol).

Here's the flow:

1. You define your standards — coding conventions, architecture rules, patterns, anti-patterns. Tag them by stack, layer, or team.

2. You import your API specs — drop in an OpenAPI/Swagger file and every endpoint gets indexed.

3. Your AI assistant calls CodeContext — when it's about to write code, it calls get_code_context and gets back only the standards relevant to the current task. No prompt bloat, no irrelevant context.

The AI doesn't just get a wall of text — it gets focused, task-specific guidance. Working on a React component? It gets your frontend standards. Writing a database migration? It gets your SQL conventions. Integrating with an external API? It gets the exact endpoints, parameters, and response schemas.

What Makes It Cool

• MCP native — works with Claude (desktop and CLI), Cursor, Windsurf, VS Code, and any MCP-compatible client. Connect once, standards everywhere.

• Smart context delivery — standards are filtered by relevance to the task, not dumped in bulk. Your AI gets signal, not noise.

• Spaces — organize standards by project, team, or domain. Scope API keys to specific spaces.

• API spec management — import OpenAPI specs and your AI can look up any endpoint on the fly.

• Team collaboration — share standards across your team so everyone's AI writes code the same way.

• Slash commands — /codecontext:implement-feature, /codecontext:code-review, /codecontext:extract-standards and more, available automatically when connected.

Getting Started

There's a free tier — 25 standards, 3 API specs, 500 MCP calls/month. Enough to try it out and see if it fits your workflow.

1. Sign up at codecontext.app

2. Add your first standards (or use /codecontext:extract-standards to have your AI analyze your codebase and generate them for you)

3. Connect your AI assistant via MCP

4. Start coding — your AI now knows your rules

Check it out and let me know what you think: codecontext.app