openslide-python
MCP ServerFreeMCP server: openslide-python
Capabilities3 decomposed
slide image retrieval
Medium confidenceThis capability allows users to retrieve high-resolution images from whole slide images (WSIs) using the OpenSlide library. It employs a model-context-protocol (MCP) server architecture to efficiently handle requests and serve images in various formats. By leveraging the OpenSlide API, it can access and manipulate slide data, making it distinct in its ability to work with large medical imaging datasets seamlessly.
Utilizes the OpenSlide library to provide direct access to slide data, enabling efficient retrieval and manipulation of high-resolution images.
More efficient than traditional image processing tools for large medical images due to its direct integration with OpenSlide.
slide metadata extraction
Medium confidenceThis capability extracts metadata from whole slide images, such as the slide's dimensions, the type of stain used, and other relevant information. It uses the OpenSlide API to access metadata properties, ensuring that users can obtain detailed information about their slides without needing to manually inspect each file. This is particularly useful for researchers and clinicians who need to manage large datasets of slides.
Integrates tightly with the OpenSlide API to provide comprehensive access to slide metadata, which is often overlooked in other tools.
Faster and more reliable than manual metadata extraction methods, especially for large datasets.
slide region analysis
Medium confidenceThis capability enables users to perform analysis on specific regions of whole slide images, such as identifying areas of interest or quantifying features within a selected region. It combines the OpenSlide library's image manipulation functions with custom analysis algorithms, allowing for tailored assessments based on user-defined criteria. This is particularly beneficial for quantitative pathology studies.
Combines image retrieval with custom analysis capabilities, allowing for tailored assessments of specific regions within slide images.
More flexible than static analysis tools, enabling user-defined criteria for region analysis.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- βpathologists needing to analyze large medical images
- βresearchers working with histopathology data
- βresearchers cataloging large slide collections
- βclinicians needing quick access to slide properties
- βpathologists conducting quantitative research
- βdata scientists analyzing medical images
Known Limitations
- β Limited to formats supported by OpenSlide; may not handle proprietary slide formats.
- β Performance may vary based on the size of the slide images.
- β Metadata extraction is limited to what is provided by the OpenSlide library; proprietary formats may not expose all metadata.
- β Analysis algorithms must be implemented separately; this tool does not include built-in analysis methods.
- β Performance may vary based on the complexity of the analysis.
Requirements
Input / Output
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MCP server: openslide-python
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