Pro MCP AI quickstart (OpenAI / Claude / Gemini)

Reference guides and how-tos for FileRise core and Pro.

Last updated Mar 3, 2026

This page is the fastest way to wire FileRise MCP into an AI app.

What FileRise gives you

FileRise MCP gives you:

  • A managed MCP runtime service (start/stop/restart in Admin).
  • Scoped MCP users/tokens mapped to a FileRise user + source + root path.
  • ACL-enforced operations and audit visibility.

What you still need to build

FileRise does not call OpenAI/Claude/Gemini for you. You provide a thin connector in your app that:

  1. Receives model tool calls.
  2. Calls FileRise MCP /v1/ops with a bearer token.
  3. Returns results back to the model.

curl examples below are for testing only, not production architecture.

1) Configure MCP in FileRise Admin

In Admin -> Gateway Shares -> MCP:

  1. Save/start MCP service (default 127.0.0.1:3030 is recommended).
  2. Create an MCP user:
    • Map to a FileRise user.
    • Set source ID.
    • Set root path scope.
  3. Copy the issued token (shown only at issue/rotation time).

2) Test MCP directly

export MCP_URL="http://127.0.0.1:3030"
export MCP_TOKEN="paste_mcp_user_token_here"

Health check:

curl -s "$MCP_URL/health"

List files in a scoped folder:

curl -s "$MCP_URL/v1/ops" \
  -H "Authorization: Bearer $MCP_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "operation":"list_files",
    "payload":{"folder":"root/photos","mode":"fast","limit":200}
  }'

3) Use one connector function for any model provider

async function fileriseMcpOp(operation, payload = {}) {
  const res = await fetch(`${process.env.MCP_URL}/v1/ops`, {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.MCP_TOKEN}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({ operation, payload })
  });
  return await res.json();
}

Use this in:

  • OpenAI function/tool calling
  • Claude tool use
  • Gemini function calling

Only the model SDK loop changes. The FileRise call stays the same.

4) Example workflow: duplicate image candidates

  1. Call list_files for folder(s).
  2. Keep image extensions (jpg, jpeg, png, webp, gif, bmp, tif, tiff, heic).
  3. Group by sizeBytes as probable duplicates.
  4. Optional: mark candidates with save_file_tag.

Note: exact duplicate detection requires hashing/content comparison in your app layer.

5) Security defaults

  • Keep MCP bind on loopback unless you have a strong network control reason.
  • Use one MCP token per integration/app.
  • Keep MCP user scopes narrow (sourceId + rootPath).
  • Rotate tokens if exposed.
  • Do not log tokens, secrets, or raw sensitive payloads.

Common confusion

Gateway Shares -> MCP in FileRise is the secure data/control plane. Your AI app is the orchestration plane.

That split is intentional:

  • FileRise enforces ACL and scope.
  • Your app chooses model/provider and prompt/tool behavior.