# Unl

Stores engineering decisions with their underlying rationale and feeds relevant context to coding agents before each step. Keeps your tools aligned on project intent.

- MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI
- Author: Unlimitless-Inc
- License: MIT · policy=link-only · description only; the file stays with the author
- Source: https://github.com/Unlimitless-Inc/unl
- Updated: 2026-10-19
- HTML: https://affpapa.org/en/nevibecode/mcp/unl

## What it does

Unl tracks technical choices and the context behind them across your coding workflow. When your agent prepares to write code, the server injects the specific guidelines that affect the immediate task. It avoids repeating project history in every prompt. You confirm every new rule.

Client libraries, the CLI, and the decision format are open source under the MIT license. The retrieval engine itself runs remotely at `api.unlimitless.ai`, meaning your project decisions pass through hosted infrastructure. Integration relies on OAuth verification instead of pasting raw API secrets into client configuration files.

## Requirements
- Remote server: `https://api.unlimitless.ai/mcp`

## Install

### Claude Code (native platform)

**Platform CLI: remote server**
```bash
claude mcp add --transport http unl https://api.unlimitless.ai/mcp
```

### Codex

**Platform CLI: remote server**
```bash
codex mcp add unl --url https://api.unlimitless.ai/mcp
```

### Cursor

**Config file**
File `.cursor/mcp.json`:
```json
{
    "mcpServers": {
        "unl": {
            "url": "https://api.unlimitless.ai/mcp"
        }
    }
}
```

### GitHub Copilot

**Config file**
File `.vscode/mcp.json`:
```json
{
    "servers": {
        "unl": {
            "type": "http",
            "url": "https://api.unlimitless.ai/mcp"
        }
    }
}
```

### Gemini CLI

**Platform CLI: remote server**
```bash
gemini mcp add -t http unl https://api.unlimitless.ai/mcp
```

## When to use it
- persist architectural decisions along with their rationale
- share decision context across Claude Code, Cursor, and Codex
- feed relevant project constraints to models before they modify files
- review agent-proposed rules prior to saving them

## Example prompts
- Check Unl for the decisions we recorded about background job processing.
- Show me why we chose synchronous exports in this service.
- Draft a new decision entry for our auth flow and send it to Unl.

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md