SchedulifyX MCP Bridge

Gets images and videos from your own machine into SchedulifyX, automatically, without a browser and without the file passing through the AI's context window.

Why this exists

MCP tool calls are JSON that flows through the model's context. Bytes therefore cannot travel through MCP — a 700 KB image is roughly 240,000 tokens as base64, which exhausts the context window before the call is even sent. Chunking does not help: the same bytes still pass through the context, just in slices.

So the file has to move out-of-band, and something with both filesystem access and network access has to move it. That is never the model, and for a remote MCP server it cannot be the server either — it has no access to your disk.

This bridge is that something. It runs locally over stdio, so it can read a path you give it and upload the bytes itself. Only the path and the resulting media ID ever reach the model — a few dozen tokens instead of a quarter of a million.

Related MCP server: XenonFlare MCP Server

What it unlocks

The case this is built for is chaining one MCP server to another:

Gemini / Veo / Runway / Sora writes an image or video to disk
        ↓
stage_latest("~/generated-images")     ← this bridge, ~40 tokens
        ↓  returns a mediaId
schedule_post(content, mediaIds: [...])  ← SchedulifyX, remote

Before this, that chain was only possible in clients that can run shell commands (Claude Code can; Claude Desktop and Cursor cannot). Now it works anywhere that can launch a local MCP server.

Install

Add it alongside the remote SchedulifyX server. In Claude Desktop's claude_desktop_config.json:

{
  "mcpServers": {
    "schedulifyx": {
      "url": "https://api.schedulifyx.com/mcp",
      "headers": { "Authorization": "Bearer sxm_your_token" }
    },
    "schedulifyx-bridge": {
      "command": "npx",
      "args": ["-y", "@schedulifyx/mcp-bridge"],
      "env": {
        "SCHEDULIFYX_TOKEN": "sxm_your_token",
        "SCHEDULIFYX_ALLOWED_DIRS": "~/Pictures,~/Downloads,~/generated-images"
      }
    }
  }
}

Use the same token for both. The bridge acts as you, with exactly the access that token has — including any brand and social-account limits set on it.

Tools

Each returns a mediaId to pass to schedule_post as mediaIds.

Security

SCHEDULIFYX_ALLOWED_DIRS is required and is the boundary: the bridge reads only from inside those directories. Paths are resolved to their real location before the check, so a symlink or .. cannot escape, and every upload goes to SchedulifyX with your token and nowhere else.

Set the narrowest set of directories that covers your generators' output.

Limits

Up to 10 GB per file. Files are streamed to storage, so memory use stays flat regardless of size.

The one case this cannot fix is a host that can neither run a local server nor reach your disk — ChatGPT's web connectors, for instance. There the browser drop-link from create_upload_link remains the only route, and no vendor has solved that, because MCP has no byte channel outside the model's context.