Kbg
What is Kbg
kbg is a custom Vue.js component designed for visualizing knowledge base graphs that are generated from MCP memory servers.
Use cases
Use cases for kbg include visualizing complex relationships in software architecture, displaying data connections in research projects, and creating interactive educational materials that illustrate knowledge structures.
How to use
To use kbg, integrate the Vue.js component into your application and provide it with the necessary data from your MCP memory server to visualize the knowledge base graphs effectively.
Key features
Key features of kbg include dynamic graph visualization, support for large datasets, and the ability to customize the appearance of graphs to enhance user experience.
Where to use
kbg can be used in various fields such as software engineering, data analysis, and educational tools where knowledge representation and visualization are essential.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Kbg
kbg is a custom Vue.js component designed for visualizing knowledge base graphs that are generated from MCP memory servers.
Use cases
Use cases for kbg include visualizing complex relationships in software architecture, displaying data connections in research projects, and creating interactive educational materials that illustrate knowledge structures.
How to use
To use kbg, integrate the Vue.js component into your application and provide it with the necessary data from your MCP memory server to visualize the knowledge base graphs effectively.
Key features
Key features of kbg include dynamic graph visualization, support for large datasets, and the ability to customize the appearance of graphs to enhance user experience.
Where to use
kbg can be used in various fields such as software engineering, data analysis, and educational tools where knowledge representation and visualization are essential.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Jump Cannon
When Cannon first started cataloging the stars, she was able to classify 1,000 stars in three years, but by 1913, she was able to work on 200 stars an hour.[20] Cannon could classify three stars a minute just by looking at their spectral patterns and, if using a magnifying glass, could classify stars down to the ninth magnitude, around 16 times fainter than the human eye can see.[8] Her work was also highly accurate.[20]
[8] Annie Cannon. She is an Astronomer. 2014. Retrieved February 18, 2014.
[20] Woman Making Index of 100,000 Stars for a Catalogue. The Danville Morning News. February 10, 1913. Retrieved April 13, 2017 – via Newspapers.com.
Browser Demo
https://ocasazza.github.io/jump-cannon/
Reference Papers
Graphviz Papers
- Graphviz and Dynagraph - Static and Dynamic Graph Drawing Tools - a condensed overview (cite)
- An open graph visualization system and its applications to software engineering - longer overview, preferred for citation (cite)
- Graph Drawing by Stress Majorization - an improved algorithm for neato (cite)
- Topological Fisheye Views for Visualizing Large Graphs - topological-based distorted views for large graphs
- A method for drawing directed graphs - dot’s algorithm (1993) (cite)
- Efficient and high quality force-directed graph drawing - sfdp’s algorithm (2005)
- Improved Circular Layouts - crossing reduction and edge bundling for circular layouts (cite)
- Efficient and High Quality Force-Directed Graph Drawing - the multiscale algorithm used in sfdp (cite)
- Implementing a General-Purpose Edge Router - edge routing in Graphviz (cite)
- Improved Force-Directed Layouts - Voronoi-based node overlap removal (cite)
- GMap: Visualizing graphs and clusters as maps - displaying graphs as maps (cite)
- Efficient Node Overlap Removal Using a Proximity Stress Model - Prism node overlap removal (cite)
- On-line Hierarchical Graph Drawing - dynadag algorithm
Graph Drawing
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Wikipedia entry. They also have a short article on Graphviz.
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graphdrawing.org - annual symposia, books, data, open problems and more
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Open Directory Project Graph Drawing entry.
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David Eppstein’s Geometry in Action, Graph Drawing section
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Graph Drawing: Algorithms for the Visualization of Graphs by Ioannis G. Tollis, Giuseppe Di Battista, Peter Eades, Roberto Tamassia
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Graph Drawing Software (Mathematics and Visualization) by M. Junger, Petra Mutzel, (Symposium on Graph Drawing 2001, Vienna)
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Drawing Graphs: Methods and Models by Michael Kaufmann, Dorothea Wagner
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Handbook of Graph Drawing and Visualization Roberto Tamassia, ed. (On-line version)
Information Visualization
- IEEE Infovis Symposia: current, past
- Information Visualization Journal
- FlowingData
- York U. Gallery of Visualization (see also Statistics and Statistical Graphics Resources).
- Stanford University course bibliography
- Stanford University Data Journalism
- Xerox PARC projects
- Software Visualization at Georgia Tech
License
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
