Stamp it
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., "@Stamp itadd a text watermark to image.jpg saying 'My Watermark'"
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.
๐ฏ Stamp it - Apply a full-screen watermark to an image
A professional image watermarking service built with FastMCP, supporting both text and image watermarks with intelligent color adaptation.
ไธญๆๆๆกฃ | English
โจ Key Features
๐ผ๏ธ Dual Watermark Modes: Support for both text and image watermarks
๐ Local File Processing: Professional local image file handling
๐จ Smart Adaptive Colors: Automatic color selection based on image brightness
๐ Tilted Watermark Effects: Customizable angle tilting (default 30ยฐ upward right)
๐ Multi-language Support: Chinese, English, Japanese, Korean and more
๐ฏ High-density Coverage: Complete coverage of every corner with no gaps
๐ High Definition: BICUBIC resampling for smooth edges
๐ Smart Saving: Auto-save in the same directory as original image
โก Performance Optimized: Font caching, intelligent scaling, memory management
๐ ๏ธ Rich Format Support: Supports 7 common image formats
Related MCP server: Visual Generator MCP
๐ Usage
MCP Client Configuration
Cherry Studio (Recommended)
Open Cherry Studio Settings
Go to Settings โ MCP Servers
Click "Add Server"
Configure MCP Server

Save and Connect
Click "Save" to add the server
The server will automatically connect
You can now use the watermark tools in Cherry Studio

Cursor
Open Cursor Settings
Use shortcut
Cmd+,(Mac) orCtrl+,(Windows/Linux)Or click Settings โ Preferences
Configure MCP Server
Find "MCP Servers" configuration option
Add the following configuration:
{
"mcpServers": {
"stampit": {
"command": "uvx",
"args": [
"mcp-stampit"
]
}
}
}Save and Restart
Save the configuration file
Restart Cursor for changes to take effect
You can now use the watermark tools in Cursor
๐ฆ Preview




๐ Installation
Using uv (Recommended)
# Install dependencies
uv pip install fastmcp pillow
# Or install using project configuration
uv pip install -e .Using pip
pip install fastmcp pillowStart the MCP Server (Standalone)
python main.pyAfter the server starts, you will see output similar to:
โญโ FastMCP 2.0 โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ ๐ฅ๏ธ Server name: Stamp it - Apply a full-screen watermark to an image โ
โ ๐ฆ Transport: STDIO โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏAvailable MCP Tools
add_text_watermark - Text Watermark
Add intelligent text watermarks to images with multi-language support and adaptive colors.
Parameters:
image_path(str): Local image file pathwatermark_text(str): Watermark text contentangle(float, optional): Watermark tilt angle, default 30ยฐ
Usage Examples:
# Basic text watermark
add_text_watermark("/Users/photos/vacation.jpg", "My Copyright")
# Custom angle
add_text_watermark("./document.png", "Confidential", angle=45)
# Multi-language watermark
add_text_watermark("photo.jpg", "Copyright ยฉ 2024 All Rights Reserved")add_image_watermark - Image Watermark
Add image watermarks to photos, supporting logos, signatures, and other images as watermarks.
Parameters:
image_path(str): Local image file pathwatermark_image_path(str): Watermark image file pathangle(float, optional): Watermark tilt angle, default 30ยฐ
Usage Examples:
# Add logo watermark
add_image_watermark("/Users/photos/product.jpg", "/Users/logos/company_logo.png")
# Custom angle logo watermark
add_image_watermark("photo.jpg", "signature.png", angle=0)
# Brand watermark
add_image_watermark("marketing_image.jpg", "brand_watermark.png", angle=15)๐จ Watermark Features
๐ Text Watermark Features
Smart Color Adaptation
Bright images: Automatically use dark watermarks (RGB 20,20,20)
Dark images: Automatically use light/white watermarks (RGB 240,240,240)
Medium brightness: Intelligently select optimal contrast colors
Multi-language Font Support
Auto-detect and load system's best Chinese fonts
Support for PingFang SC, Microsoft YaHei, SimHei, etc.
Perfect display of Chinese, Japanese, Korean, and English
High-quality Rendering
Font caching for improved performance
BICUBIC resampling for smooth edges
Centered rendering with excellent rotation effects
๐ผ๏ธ Image Watermark Features
Smart Scaling: Auto-scale to appropriate size (default 15%)
Opacity Control: Automatic opacity adjustment without affecting original image
Aspect Ratio Preservation: Maintain watermark image aspect ratio
High-quality Scaling: Use LANCZOS algorithm for clarity
๐ฏ Layout Algorithm
Complete Coverage: Start from outside image boundaries for 100% coverage
Staggered Arrangement: Odd-even row offset for more natural visual effect
Dense Distribution: Optimized spacing algorithm, 40% higher density than traditional methods
Edge Handling: Complete watermark coverage in all four corners
๐ File Output
Save Rules
Save Location: Auto-save in the same directory as original image
Naming Convention: Original filename +
_watermark+ extensionFormat Preservation: Maintain original image format and quality
Optimized Saving: Enable compression optimization to reduce file size
Output Examples
Input: /Users/photos/vacation.jpg
Output: /Users/photos/vacation_watermark.jpg
Input: ./designs/logo.png
Output: ./designs/logo_watermark.png
Input: document.pdf.png
Output: document.pdf_watermark.png๐ ๏ธ Supported Image Formats
Format | Extensions | Read | Save | Transparency | Optimized |
JPEG | .jpg, .jpeg | โ | โ | โ | โ |
PNG | .png | โ | โ | โ | โ |
GIF | .gif | โ | โ | โ | โ |
BMP | .bmp | โ | โ | โ | โ |
TIFF | .tiff, .tif | โ | โ | โ | โ |
WebP | .webp | โ | โ | โ | โ |
๐ Multi-language Font Support
Supported Languages
Chinese: Simplified & Traditional Chinese
Japanese: ใฒใใใชใใซใฟใซใใๆผขๅญ
Korean: ํ๊ธ (Hangul)
English: Latin character set
Others: Most Unicode characters
Font Priority
macOS System:
PingFang SC (Apple's default Chinese font)
STHeiti Light (Chinese typography)
Hiragino Sans GB (Winter Blue font)
Arial Unicode (Universal Unicode font)
Windows System:
Microsoft YaHei
SimSun
SimHei
Linux System:
DejaVu Sans
Liberation Sans
Noto Sans CJK
WenQuanYi Zen Hei
๐ Project Structure
stampit/
โโโ main.py # Main program and MCP server
โโโ pyproject.toml # Project configuration
โโโ README.md # English project documentation
โโโ README_CN.md # Chinese project documentation
โโโ uv.lock # Dependency lock file
โโโ LICENSE # License file๐งช Quick Testing
Test Text Watermark
# 1. Start server
python main.py
# 2. Call in MCP client
add_text_watermark("path/to/your/image.jpg", "Test Watermark")Test Image Watermark
# 1. Prepare a logo image
# 2. Call in MCP client
add_image_watermark("path/to/your/photo.jpg", "path/to/logo.png")โ๏ธ Technical Details
Core Algorithms
Brightness Calculation: Grayscale conversion + pixel average algorithm
Color Adaptation: Four-tier classification system based on brightness thresholds
Position Calculation: Staggered grid + edge offset algorithm
Rendering Optimization: BICUBIC/LANCZOS resampling technology
Performance Optimization
Font Caching: Avoid repeated font file loading
Smart Scaling: Brightness calculation using 50x50 small images for speed
Memory Management: Timely release of temporary layers and cache
Batch Processing: Support for efficient batch image processing
Quality Assurance
Edge Smoothing: Use high-quality resampling algorithms
Color Fidelity: Preserve original image color space and mode
Transparency Handling: Proper RGBA channel processing
Format Compatibility: Smart conversion between different image formats
๐ง Advanced Configuration
You can adjust parameters by modifying the WatermarkConfig class:
class WatermarkConfig:
DEFAULT_FONT_SIZE = 36 # Default font size
DEFAULT_ANGLE = 30 # Default tilt angle
SPACING_X_FACTOR = 1.1 # Horizontal spacing multiplier
SPACING_Y_FACTOR = 0.9 # Vertical spacing multiplier
BRIGHTNESS_THRESHOLDS = { # Brightness thresholds
'very_bright': 180,
'medium': 120,
'dark': 60
}Custom Parameter Suggestions
Dense Watermarks: Lower spacing multipliers (0.8, 0.7)
Sparse Watermarks: Higher spacing multipliers (1.5, 1.3)
Large Fonts: Increase font size (48, 54)
Small Fonts: Decrease font size (24, 30)
๐๏ธ Usage Tips
Text Watermark Tips
Copyright Info: Use "ยฉ 2024 Company Name" format
Multi-language: Mixed Chinese-English works better
Angle Selection: 30ยฐ most natural, 45ยฐ more prominent, 0ยฐ for documents
Image Watermark Tips
Logo Design: Use transparent background PNG format
Size Control: Logo shouldn't be too large, recommend within 15% of original
Color Matching: Choose logo colors with appropriate contrast to original image
๐ก Best Practices
Batch Processing Recommendations
# Recommended batch processing method
images = ["photo1.jpg", "photo2.jpg", "photo3.jpg"]
watermark_text = "ยฉ 2024 My Company"
for image_path in images:
result = add_text_watermark(image_path, watermark_text)
print(result)Performance Optimization Suggestions
Use same font size in batches to leverage font caching
Avoid frequent angle changes to reduce computational overhead
Use small-sized image watermarks to improve processing speed
๐ License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
๐ค Contributing
Issues and Pull Requests are welcome!
Contributing Guidelines
Fork the project
Create a feature branch
Commit your changes
Submit a Pull Request
๐ Technical Support
For questions or suggestions:
Submit GitHub Issues
Check project documentation
Contact development team
๐ Thank you for using Stamp it!
Available Tools
2 toolsadd_image_watermarkA
ไธบๅพ็ๆทปๅ ๅพ็ๆฐดๅฐ
Args: image_path: ๆฌๅฐๅพ็ๆไปถ่ทฏๅพ watermark_image_path: ๆฐดๅฐๅพ็ๆไปถ่ทฏๅพ angle: ๆฐดๅฐๅพๆ่งๅบฆ๏ผ้ป่ฎค30ๅบฆ๏ผ
Returns: ๅค็ๅ็ๅพ็ไฟๅญ่ทฏๅพไฟกๆฏ
| Name | Required | Description | Default |
|---|---|---|---|
| image_path | Yes | ||
| watermark_image_path | Yes | ||
| angle | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only mentions adding a watermark and saving the result, but does not disclose whether the original file is modified, what the output format is, or any permissions needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with a one-line purpose statement followed by a clear Args section. No redundant information, and the structure is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, return values need not be detailed, but the description lacks details on watermark positioning, image format compatibility, or error handling. The tool's behavior is not fully specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description includes an Args section that explains each parameter: image_path is a local file path, watermark_image_path is the watermark image path, and angle has a default of 30 degrees. This adds significant meaning beyond the schema property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it adds an image watermark to a picture, distinguishing it from the sibling tool 'add_text_watermark' which adds text watermarks. The verb 'add' and resource 'image watermark' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for image watermarking but does not explicitly state when to use this tool over the sibling 'add_text_watermark'. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_text_watermarkB
ไธบๅพ็ๆทปๅ ๆๅญๆฐดๅฐ
Args: image_path: ๆฌๅฐๅพ็ๆไปถ่ทฏๅพ watermark_text: ๆฐดๅฐๆๅญๅ ๅฎน angle: ๆฐดๅฐๅพๆ่งๅบฆ๏ผ้ป่ฎค30ๅบฆ๏ผ
Returns: ๅค็ๅ็ๅพ็ไฟๅญ่ทฏๅพไฟกๆฏ
| Name | Required | Description | Default |
|---|---|---|---|
| image_path | Yes | ||
| watermark_text | Yes | ||
| angle | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions it returns the processed image path but does not disclose behavioral traits such as whether the original image is modified, required image formats, or side effects. No annotations are provided to compensate, so the description carries the full burden and falls short.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear structure (Args, Returns). It uses no unnecessary words and fits the tool's simplicity. However, it could be more structured for multilingual clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool, the description covers the purpose and basic parameters. The return value is mentioned. Without the output schema, the description is adequate but does not elaborate on possible errors, output format, or other complexities. It meets the minimum viable standard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides explanations for all three parameters: image_path (local file path), watermark_text (text content), and angle (tilt angle, default 30). This adds meaning beyond the schema's type/default definitions, partially compensating for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'ไธบๅพ็ๆทปๅ ๆๅญๆฐดๅฐ' (add text watermark to image), which is a specific verb+resource combination. It also distinguishes from the sibling tool 'add_image_watermark' by specifying 'text watermark' versus an image watermark.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives (e.g., add_image_watermark) or any exclusions. The usage is implied by the tool name and description, but the agent receives no context about preferences or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.7- First observed
add_image_watermark - First observed
add_text_watermark
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one adds an image watermark, the other adds a text watermark. There is no ambiguity or overlap between them.
Both tools follow a consistent verb_noun pattern (add_image_watermark, add_text_watermark) with underscore separation, making naming predictable and clear.
With only 2 tools, the server is very focused on watermarking. While minimal, it covers the two primary watermark types, so the count feels appropriate for a simple utility.
The server covers the core watermarking operations (image and text). Missing advanced options like opacity or position, but the essential functionality is complete for a basic stamping tool.
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