generate_imageLABSCO SUMMARY
Built for a chat window, not an API script.
Parallel batches, editing images you attached to the message, and a history grid you can branch variations from are all shaped around a conversation rather than a request/response loop. Video is the part to plan around: renders take minutes and long clips up to about an hour, so the tool returns a pending request_id and the result survives closing the chat. Batch cheap drafts first, then enhance the one you want.
What it is
The hosted FLUX MCP server from Black Forest Labs. It exposes the FLUX toolkit — text-to-image, editing, multi-reference composition, virtual try-on, video and history — over a remote OAuth connection, so there is no API code and no key pasted into the conversation.
What you get
- 1–8 images generated in parallel from one prompt, covering text-to-image, edits, multi-reference composition, style transfer, inpainting-style edits and outpainting —
generate_image - Virtual try-on that dresses a person or pet in a garment, hat, sunglasses, shoes or bag from a reference image, preserving face, hair and pose —
vto - 1–4 videos in parallel with FLUX 3 — text-to-video, image-to-video from keyframes, or continuation of an existing clip, 5–20 seconds with synchronized audio —
generate_video - A draft video re-rendered at full quality from the same composition, seed and prompt plan —
enhance_video - More images in the same direction as an earlier result, identified by
request_id, defaulting to 4 and capped at 8 —generate_variations - Past generations browsed as a thumbnail grid with per-tile actions, keyset pagination and date filters —
get_history - Your remaining BFL credit balance —
get_credits - Model choice on
generate_image:flux2_pro_previewby default,flux2_maxfor final assets,flux2_klein_9b_previewandflux2_klein_4bfor speed,flux2_flexfor readable typography; the full catalog is also thebfl://modelsresource
Requirements
A BFL account, authorized over OAuth, and a BFL organization to bill — you pay Black Forest Labs directly, with no middleman and no shared quota. Connect to https://mcp.bfl.ai over streamable HTTP: in Claude it is Settings → Connectors → Add custom connector; in Claude Code, claude mcp add --transport http FLUX https://mcp.bfl.ai; in Codex, codex mcp add flux --url https://mcp.bfl.ai then codex mcp login flux. Clients that only do stdio can bridge with npx -y mcp-remote https://mcp.bfl.ai, which caches tokens to ~/.mcp-auth/. Server version 1.2.0, MIT licensed.
Setup effort
One command, then sign in — claude mcp add --transport http FLUX https://mcp.bfl.ai, then approve the OAuth sign-in
USE CASES
Choosing between options instead of iterating one at a time
Ask for four variants of the same brief with different lighting and mood, then branch more from whichever lands.
Changing one thing in a photo you already have
Attach the image and describe the edit, telling it to preserve the rest of the composition exactly.
Seeing a garment on a specific person
Attach a photo and a reference of the item; face, hair and pose stay put and only the worn item changes.
Getting a clip without burning a full-quality render
Generate several fast drafts with different camera moves, pick one, and re-render just that one at full quality.
Coming back to something you made last week
Browse the history grid and edit, vary or download any past result.
7 tools
Listed in project docs. Your client may show a different list.
vtogenerate_videoenhance_videogenerate_variationsget_historyget_creditsBEFORE YOU INSTALL
What to know first
Tools you get
7 tools named in the project's documentation.
Requires
- A client that can reach a remote MCP server over HTTP
- A BFL account (bfl.ai), signed in over OAuth when you connect, with an organization that has enough credits to bill
INSTALLATION
Connect your client
Server setup
claude mcp add
Claude Code
claude mcp add --transport http FLUX https://mcp.bfl.aiHosted endpoint
https://mcp.bfl.aiAdd this hosted endpoint to your MCP client, then sign in.
MCP Clients
Claude Desktop, Claude.ai
Open Settings → Connectors at https://claude.ai/settings/connectors.
Click Add custom connector.
Name it FLUX, URL https://mcp.bfl.ai.
Click Connect, sign in, choose the BFL organization to bill.
Cursor
{
"mcpServers": {
"FLUX": {
"url": "https://mcp.bfl.ai"
}
}
}Codex
[mcp_servers.flux]
url = "https://mcp.bfl.ai"Windsurf
{
"mcpServers": {
"FLUX": {
"serverUrl": "https://mcp.bfl.ai"
}
}
}Any MCP client — stdio bridge
{
"mcpServers": {
"FLUX": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.bfl.ai"
]
}
}
}