Remote MCP

Connect Aibubu to Claude Code, Codex, Cursor, VS Code, Cherry Studio and Claude Desktop with an MCP URL and an API key; nothing to install.

Aibubu runs a remote MCP server over Streamable HTTP, authenticated with your API key:

Item	Value
URL	`https://aibubu.ai/mcp`
Auth	Header `Authorization: Bearer sk_aibubu_xxx`
Scopes	Read tools need `v1:read`; upload and generation need `v1:generate`

MCP shares authentication, billing and the daily credit limit with the /v1 API.

Tools

Tool	Kind	Purpose
`list_models`	Read	List available models, filterable by `image`, `video`, `text` or keyword
`get_model`	Read	Show a model's parameter schema and pricing notes
`quote`	Read	Estimate credits for given parameters without creating a task
`get_balance`	Read	Show available credits
`upload_image`	Write	Upload a base64-encoded reference image (up to 30 MiB per request, so about 22 MB of image) and get a URL valid for about 15 minutes, for the next generation
`generate_image`	Write, spends credits	Submit an image generation task; pass `idempotency_key` so network retries never double-submit
`generate_video`	Write, spends credits	Submit a video generation task
`get_task`	Read	Get task status and results
`wait_task`	Read	Wait up to about 60 seconds on the server; returns the current state if unfinished, so call it again

Generation tools are marked as write operations, so most clients ask you to confirm before calling them.

Configure your client

These examples read the key from AIBUBU_API_KEY. Set it first:

export AIBUBU_API_KEY=sk_aibubu_your_api_key

Claude Code

claude mcp add --transport http aibubu https://aibubu.ai/mcp \
  --header "Authorization: Bearer $AIBUBU_API_KEY"

Run claude mcp list to confirm aibubu is connected.

Codex

Edit ~/.codex/config.toml:

[mcp_servers.aibubu]
url = "https://aibubu.ai/mcp"
bearer_token_env_var = "AIBUBU_API_KEY"

Cursor

Edit ~/.cursor/mcp.json (global) or .cursor/mcp.json in your project:

{
  "mcpServers": {
    "aibubu": {
      "url": "https://aibubu.ai/mcp",
      "headers": {
        "Authorization": "Bearer ${env:AIBUBU_API_KEY}"
      }
    }
  }
}

VS Code

Create .vscode/mcp.json in your project. This prompts for the key on first connect and keeps it out of the file:

{
  "inputs": [
    {
      "type": "promptString",
      "id": "aibubu-api-key",
      "description": "Aibubu API Key",
      "password": true
    }
  ],
  "servers": {
    "aibubu": {
      "type": "http",
      "url": "https://aibubu.ai/mcp",
      "headers": {
        "Authorization": "Bearer ${input:aibubu-api-key}"
      }
    }
  }
}

Cherry Studio

Under Settings → MCP Servers → Add Server:

Type: Streamable HTTP (streamableHttp)
URL: https://aibubu.ai/mcp
Headers: Authorization=Bearer sk_aibubu_your_api_key

Claude Desktop

Claude Desktop's config file only runs local commands, so bridge with mcp-remote (needs Node.js). Edit claude_desktop_config.json:

{
  "mcpServers": {
    "aibubu": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://aibubu.ai/mcp", "--header", "Authorization:${AIBUBU_AUTH}"],
      "env": {
        "AIBUBU_AUTH": "Bearer sk_aibubu_your_api_key"
      }
    }
  }
}

Keep Authorization:${AIBUBU_AUTH} without a space; the space goes inside the environment variable's value.

Verify

Ask your client:

Use aibubu to list the video models and show my credit balance

If you get a model list and a balance, the connection works.

Troubleshooting

Symptom	Fix
Connection fails with `401`	The key isn't reaching the header. Check the variable is set where the client starts
Generation returns `scope_forbidden`	The key lacks `v1:generate`
Generation returns `insufficient_credits`	Not enough credits; top up and retry
`wait_task` says the task is still running	Expected. Videos usually take a few minutes; let the client call `wait_task` or `get_task` again

Remote MCP

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