# Using Skills with Any LLM

> Publish once. Use your Aerostack skills with Claude, ChatGPT, Gemini, or any LLM — via MCP, OpenAI function format, or Gemini tool declarations.

The same skill works with any LLM. Aerostack generates the right protocol format automatically — you publish once, your skill is accessible from Claude, ChatGPT, and Gemini without rebuilding anything.

---

## The Problem with Today's Tool Ecosystem

Most AI tools are tied to a single LLM platform:

| Skill format | Claude | ChatGPT | Gemini |
|-------------|--------|---------|--------|
| OpenAI Actions (GPT Store) | ❌ | ✅ | ❌ |
| MCP server | ✅ | ✅* | ❌ |
| Gemini Extensions | ❌ | ❌ | ✅ |

*OpenAI added MCP support in 2026, so MCP servers now work with both Claude and ChatGPT. Gemini still requires its own format.

Aerostack handles the translation layer — one skill definition, every format.

---

## Option 1: MCP (Claude, Cursor, Windsurf, ChatGPT)

The primary way to use skills is through your workspace gateway. Configure it once in your editor — all installed skills appear as MCP tools:

```json
{
  "mcpServers": {
    "my-workspace": {
      "url": "https://gateway.aerostack.dev/ws/my-workspace",
      "headers": { "Authorization": "Bearer mwt_…" }
    }
  }
}
```

**Works with:**
- Claude (via Claude Code, claude.ai with MCP beta)
- Cursor
- Windsurf
- VS Code Copilot
- ChatGPT (via MCP connector, 2026+)
- Any editor that supports MCP

Install a skill → it appears through this URL immediately.

---

## Option 2: OpenAI Function Format

If you're using the OpenAI API directly in your code (not via an editor), fetch your skills as OpenAI function definitions:

```
GET https://gateway.aerostack.dev/ws/{workspaceSlug}/openai-tools
Authorization: Bearer mwt_...
```

Returns:

```json
[
  {
    "type": "function",
    "function": {
      "name": "github__create_issue",
      "description": "[github] Create a new issue on a GitHub repository",
      "parameters": {
        "type": "object",
        "properties": {
          "owner": { "type": "string", "description": "Repository owner" },
          "repo": { "type": "string", "description": "Repository name" },
          "title": { "type": "string", "description": "Issue title" },
          "body": { "type": "string", "description": "Issue body (markdown)" }
        },
        "required": ["owner", "repo", "title"]
      }
    }
  }
]
```

Use in your OpenAI API calls:

```typescript

const client = new OpenAI();

// Fetch your installed skills in OpenAI format
const toolsResponse = await fetch('https://gateway.aerostack.dev/ws/my-workspace/openai-tools', {
  headers: { Authorization: `Bearer ${process.env.MWT_TOKEN}` }
});
const tools = await toolsResponse.json();

// Use in ChatCompletion
const response = await client.chat.completions.create({
  model: 'gpt-4o',
  tools,
  messages: [{ role: 'user', content: 'Create a GitHub issue for the login bug' }]
});

// When OpenAI calls a tool, route it back through Aerostack gateway
if (response.choices[0].finish_reason === 'tool_calls') {
  const toolCall = response.choices[0].message.tool_calls[0];
  const result = await callAerostackGateway(toolCall.function.name, JSON.parse(toolCall.function.arguments));
  // ...
}
```

---

## Option 3: Gemini Tool Declarations

For Google Gemini API users:

```
GET https://gateway.aerostack.dev/ws/{workspaceSlug}/gemini-tools
Authorization: Bearer mwt_...
```

Returns Gemini-compatible function declarations:

```json
[
  {
    "name": "github__create_issue",
    "description": "[github] Create a new issue on a GitHub repository",
    "parameters": {
      "type": "OBJECT",
      "properties": {
        "owner": { "type": "STRING", "description": "Repository owner" },
        "repo": { "type": "STRING", "description": "Repository name" },
        "title": { "type": "STRING", "description": "Issue title" }
      },
      "required": ["owner", "repo", "title"]
    }
  }
]
```

Use with the Gemini API:

```typescript

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);

// Fetch tools in Gemini format
const toolsResponse = await fetch('https://gateway.aerostack.dev/ws/my-workspace/gemini-tools', {
  headers: { Authorization: `Bearer ${process.env.MWT_TOKEN}` }
});
const functions = await toolsResponse.json();

const model = genAI.getGenerativeModel({
  model: 'gemini-1.5-pro',
  tools: [{ functionDeclarations: functions }]
});
```

---

## Option 4: Install per Editor (Manual)

If you prefer to install skills directly into your editor's config rather than via a shared workspace:

```bash
# Cursor
aerostack skill install @johndoe/github-skill --editor cursor

# Windsurf
aerostack skill install @johndoe/github-skill --editor windsurf

# Claude Code
aerostack skill install @johndoe/github-skill --editor claude-code

# VS Code
aerostack skill install @johndoe/github-skill --editor vscode
# → writes entry to .vscode/mcp.json
```

---

## Which Approach to Use

| Situation | Recommended approach |
|-----------|---------------------|
| Using Claude Code, Cursor, or Windsurf | Workspace gateway (MCP) |
| Building with the OpenAI API in code | `/openai-tools` endpoint |
| Building with the Gemini API in code | `/gemini-tools` endpoint |
| Team setup where everyone needs the same skills | Shared workspace gateway |
| Personal setup, specific editor | `--editor` flag |

The workspace gateway (Option 1) is the most powerful because:
- One config, all editors
- Add skills without touching editor configs
- Works with MCP-compatible LLMs automatically

---

## Publish Once, Reach All LLMs

When you publish a skill on Aerostack, the tool definitions in your `tools[]` array use JSON Schema — the same schema format used by MCP, OpenAI, and Gemini (with minor formatting differences). Aerostack generates the format-specific responses at request time.

You write the tool once. Every LLM can use it.