fapihub-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@fapihub-mcp remove the background from assets/product.jpg"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
FAPIHUB MCP Server
An MCP server that gives AI agents (Claude Code, Claude Desktop, Cursor, VS Code, Windsurf and others) background-removal tools from FAPIHUB.
Ask your agent things like:
Remove the background from
assets/product.jpgPut every photo in
./teamon a solid#F5F5F5backgroundBlur the background of
portrait.pngand add a soft drop shadow tologo.png
The server reads images from your disk, sends them to the FAPIHUB API and saves the results next to the originals.
Preview
One photo, every tool:
Related MCP server: obrobka-mcp
Tools
Tool | What it does | Options |
| Transparent PNG cutout of the subject |
|
| Black-and-white subject mask |
|
| Keeps the subject sharp and blurs the background |
|
| Replaces the background with a solid color |
|
| Replaces the background with a vertical gradient |
|
| Cutout with a drop shadow |
|
| Your plan, its limits, and requests used and remaining |
Every image tool takes image_path (JPG, PNG, WEBP, BMP or GIF, 1 KB to 10 MB) and an optional output_path. Without output_path, the result is saved as <name>_<operation>.<ext> beside the input and never overwrites an existing file.
Colors can be hex (#FF8C00, #FF8C0080) or RGB(A) (255, 140, 0 or 255, 140, 0, 128).
Each image tool call uses one request from your FAPIHUB plan. Invalid inputs (missing file, wrong format, bad size) are caught locally before anything is sent, so they don't use quota. get_usage is free, so agents can check how much quota is left before a large batch:
Plan: Pro (monthly, $15.00)
Status: active
Requests: 1,240 of 7,500 used (16.5%), 6,260 remaining
Successful: 1,225, failed (4xx, counted): 15
Rate limit: 60 requests per minute
Billing period: 2026-10-01 to 2026-11-01 (quota resets on 2026-11-01)Setup
Create an API key in your FAPIHUB dashboard.
Install uv, which provides
uvx.Add the server to your client using one of the configurations below.
Claude Code
claude mcp add fapihub -e FAPIHUB_API_KEY=bg_live_sk_... -- uvx --from git+https://github.com/Firdavs-coder/fapihub-mcp fapihub-mcpClaude Desktop, Cursor, Windsurf and other JSON-configured clients
Add this to your client's MCP config (claude_desktop_config.json, .cursor/mcp.json, etc.):
{
"mcpServers": {
"fapihub": {
"command": "uvx",
"args": ["--from", "git+https://github.com/Firdavs-coder/fapihub-mcp", "fapihub-mcp"],
"env": {
"FAPIHUB_API_KEY": "bg_live_sk_..."
}
}
}
}VS Code
Add this to .vscode/mcp.json:
{
"servers": {
"fapihub": {
"command": "uvx",
"args": ["--from", "git+https://github.com/Firdavs-coder/fapihub-mcp", "fapihub-mcp"],
"env": {
"FAPIHUB_API_KEY": "bg_live_sk_..."
}
}
}
}Configuration
Environment variable | Required | Default |
| Yes | |
| No |
|
| No |
|
Development
git clone https://github.com/Firdavs-coder/fapihub-mcp
cd fapihub-mcp
uv sync
uv run pytestTo try the server against a local FAPIHUB instance:
FAPIHUB_API_KEY=bg_live_sk_... FAPIHUB_BASE_URL=http://127.0.0.1:8000 uv run fapihub-mcpLicense
MIT
Available Tools
7 toolsadd_shadowB
Cut out the subject and add a drop shadow behind it on a transparent background.
Inputs: image_path (required), offset_x, offset_y, blur_radius, +2 more. Returns: result
blur_backgroundA
Keep the subject sharp and blur the background (portrait-style bokeh).
Inputs: image_path (required), radius, output_path. Returns: result
color_backgroundB
Replace the background with a solid color.
Inputs: color (required), image_path (required), output_path. Returns: result
create_maskB
Create a black-and-white subject mask (white = subject, black = background) for an image.
Inputs: image_path (required), model, output_path. Returns: result
get_usageARead-onlyIdempotent
Show the FAPIHUB plan, its limits, and how many requests are used and remaining.
Free: does not use quota. Check it before processing many images.
Inputs: no named parameters. Returns: result
gradient_backgroundB
Replace the background with a vertical gradient from top_color to bottom_color.
Inputs: top_color (required), image_path (required), bottom_color (required), output_path. Returns: result
remove_backgroundB
Remove the background from an image, producing a transparent PNG cutout of the subject.
Inputs: image_path (required), model, output_path. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 7 tools
Each tool has a clearly distinct image-editing operation: background removal, mask creation, background blur, solid color replacement, gradient replacement, shadow addition, and usage inspection. While blur/color/gradient all manipulate backgrounds, their descriptions make the output differences explicit, and create_mask versus remove_background is also clear.
Most tools follow a verb_noun pattern such as remove_background, create_mask, blur_background, color_background, and add_shadow. The one deviation is gradient_background, which reads more like noun_noun than verb_noun, but the overall convention remains readable and predictable.
Seven tools is well-scoped for an image background processing API. Each tool corresponds to a meaningful operation, and there is no redundant filler.
The surface covers the core background-manipulation workflows: removal, masking, blur, solid color, gradient, shadow, plus usage inspection. A custom image background replacement or compositing tool would round it out further, but the existing set covers the primary domain operations.
Maintenance
Related MCP Connectors
Image & PDF tools for AI agents: compress, convert, resize, PDF, AI vision, pipeline.
Compress, convert, resize, crop, upscale, OCR and remove backgrounds from images.
Video, audio, and image processing for AI agents: convert, transcribe, upscale - 150+ operations.
LLM chat, text tools, image generation, editing, batch image jobs, and asynchronous video generation
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to perform image processing tasks such as sprite sheet splitting, resizing, cropping, and batch operations on local images.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to process images locally via file paths—converting, resizing, removing backgrounds, smart cropping, upscaling, reading or stripping metadata, and batch processing—without files ever leaving the device.MIT
- AlicenseAqualityCmaintenanceEnables AI agents to perform local image operations such as circle cropping, cropping, resizing, compressing, converting, and inspecting images without uploading files or making network calls.761 npmMIT
- AlicenseAqualityBmaintenanceLocal file tools for agents. Read and convert documents (DOCX, PDF, HWP, HWPX, EML), edit PDFs, resize and clean images, cut out backgrounds, make QR codes. Nothing is uploaded.65MIT