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Documentation Index

Fetch the complete documentation index at: https://hubify.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

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Bring Your Own Agent

Hubify Labs deliberately does NOT require the dedicated hubify CLI. The CLI is one nice path. The other path, the one most Captains actually use, is your existing AI coding agent. Every skill in Skills Overview is a markdown file plus a Hubify MCP server. If your agent reads MCP servers AND reads system-prompt-style markdown skills, you’re done.

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What works today

AgentMCP supportSkills supportStatus
Claude CodeNative (claude mcp add ...)Native (~/.claude/skills/)First-class, setup guide
CursorNative (.cursor/mcp.json)Via .cursor/rules/*.mdcFirst-class, setup guide
Codex (OpenAI CLI)Via ~/.codex/config.json MCP blockVia slash-command filesWorking, see below
Cline (VS Code)Native MCPVia custom-instructions fieldWorking
ContinueNative MCPVia .continue/rulesWorking
Zed AINative MCP (assistant 2.0+)Via prompts libraryWorking
AiderNone todayVia --read system promptManual, the MCP tools are unavailable

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Codex (OpenAI CLI) setup

OpenAI’s codex CLI ships MCP support. Add Hubify the same way you’d add any MCP server.
1

Install the CLI

npm install -g hubify-labs
Requires hubify-labs 2.0.0+ for the hubify mcp subcommand.
2

Edit ~/.codex/config.json

{
  "mcpServers": {
    "hubify": {
      "command": "hubify",
      "args": ["mcp"],
      "env": {
        "CONVEX_URL": "https://your-deployment.convex.cloud",
        "HUBIFY_LAB_SLUG": "your-lab-slug"
      }
    }
  }
}
3

Verify

codex
> /hubify-status
Should return your real lab status and recent events.

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Cline (VS Code) setup

1

Install the CLI

npm install -g hubify-labs
2

Add to Cline MCP settings

Open Cline > Settings > MCP Servers and add:
{
  "hubify": {
    "command": "hubify",
    "args": ["mcp"],
    "env": {
      "CONVEX_URL": "https://your-deployment.convex.cloud",
      "HUBIFY_LAB_SLUG": "your-lab-slug"
    }
  }
}
3

Add skill prompts

Cline doesn’t have a true slash-command system, but you can paste skill bodies into Custom Instructions and trigger them by phrase (“Run hubify-status”).

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Continue setup

1

Install the CLI

npm install -g hubify-labs
2

Edit ~/.continue/config.yaml

mcpServers:
  - name: hubify
    command: hubify
    args: ["mcp"]
    env:
      CONVEX_URL: https://your-deployment.convex.cloud
      HUBIFY_LAB_SLUG: your-lab-slug
3

Add skills to .continue/rules/

Continue reads .continue/rules/*.md as system-prompt rules. Drop skills there; trigger by phrase.

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Zed AI setup

1

Install the CLI

npm install -g hubify-labs
2

Add to Zed settings

Open ~/.config/zed/settings.json:
{
  "context_servers": {
    "hubify": {
      "command": {
        "path": "hubify",
        "args": ["mcp"],
        "env": {
          "CONVEX_URL": "https://your-deployment.convex.cloud",
          "HUBIFY_LAB_SLUG": "your-lab-slug"
        }
      }
    }
  }
}
3

Add skills to Zed prompts library

Open the prompts library (cmd-shift-p > “open prompts library”) and paste skill bodies as new prompts.

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Aider (no MCP yet)

Aider does not support MCP. You can still wire some skills manually:
  1. Install the CLI: npm install -g hubify-labs
  2. Drop a system prompt: aider --read ~/.aider/hubify-context.md where the context file is the skill body plus Use \hubify` CLI commands instead of MCP tools.`
  3. Aider will hubify status, hubify experiments, etc. shell out for the same data.
This is a workaround. If you want first-class Aider support, open an issue, we’ll add a thin shim.

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Why this works

The whole architecture is intentional:
  • MCP server = the data layer. Speaks one protocol (MCP). Every tool that adopts MCP gets Hubify for free.
  • Skills = the prompt layer. Plain markdown. Trivial to port between agents.
  • Hubify Cloud (Convex + Gateway + RunPod) = the source of truth. CLI, MCP, web app, and lab-site preview all read the same data.
You never have to choose between “use Claude Code” and “use Hubify.” Both at once is the default.

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See also