Capabilities5 decomposed
github repository star history visualization generation
Medium confidenceGenerates time-series SVG charts visualizing GitHub repository star count history by querying GitHub's public API data and rendering historical trends as vector graphics. The service fetches star count snapshots across repository lifetime and plots them on a date-based timeline, producing embeddable SVG output suitable for documentation, README files, and web pages without requiring client-side charting libraries.
Generates embeddable SVG charts directly from GitHub API without requiring client-side JavaScript charting libraries, enabling lightweight README embedding and static site integration. Uses server-side rendering to produce optimized vector graphics with minimal payload compared to raster image alternatives.
Lighter-weight than client-side charting solutions (Chart.js, D3.js) because rendering happens server-side, producing pure SVG output that embeds directly in markdown without JavaScript dependencies or external CDN calls.
multi-repository comparative star history visualization
Medium confidenceAccepts comma-separated or pipe-delimited repository identifiers in a single API request and renders overlaid time-series charts comparing star growth trajectories across multiple projects on a unified timeline. This enables side-by-side growth pattern analysis without requiring multiple API calls or client-side chart composition.
Overlays multiple repository star histories on a single timeline with synchronized date axes, enabling direct visual comparison of growth patterns without requiring external charting tools or post-processing. Server-side composition ensures consistent styling and automatic legend generation.
More convenient than manually creating separate charts and compositing them in design tools because all repositories render on unified axes with automatic color assignment and legend, reducing preparation time from hours to seconds.
date-based star history timeline rendering
Medium confidenceRenders star count history as a time-series line chart with dates on the X-axis and cumulative star count on the Y-axis, showing the progression of repository popularity over calendar time. The service interpolates GitHub API data points and produces a smooth or stepped visualization depending on data granularity, suitable for identifying growth inflection points and seasonal patterns.
Automatically maps GitHub star data to calendar dates without requiring manual data extraction or transformation, rendering directly as SVG with axis labels and gridlines. Handles repositories with sparse historical data by interpolating or stepping between data points based on available API snapshots.
Simpler than building custom time-series charts with D3.js or Plotly because date mapping and axis scaling are handled server-side, eliminating need for client-side date parsing and normalization logic.
embeddable svg chart url generation with query parameters
Medium confidenceProvides a parameterized HTTP endpoint that accepts repository identifiers and chart type specifications as URL query parameters, returning a direct SVG URL suitable for embedding in markdown, HTML, and documentation platforms. The stateless design enables URL-based sharing and dynamic chart generation without backend state management.
Stateless query-parameter-based API design enables direct URL embedding without requiring API key management, authentication headers, or backend state — charts are generated on-demand from URL parameters alone. This pattern allows markdown-native integration without JavaScript or build-time processing.
More portable than APIs requiring authentication tokens or POST bodies because the entire request encodes as a simple URL, enabling copy-paste embedding in any markdown or HTML context without additional tooling.
github api data aggregation and historical star count retrieval
Medium confidenceInternally queries GitHub's public REST API to fetch repository metadata and historical star count data, aggregating snapshots across the repository's lifetime to construct time-series datasets. The service manages API rate limits, caches historical data, and reconstructs star count progression from available API endpoints without requiring users to handle GitHub authentication or pagination.
Abstracts GitHub API complexity by managing authentication, rate limiting, and historical data aggregation server-side, exposing only a simple repository identifier parameter. Caches historical snapshots to avoid redundant API calls and rate limit exhaustion when generating multiple visualizations.
Eliminates need for users to obtain GitHub API tokens or manage pagination because the service handles all GitHub API interaction internally, reducing integration friction compared to direct GitHub API consumption.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
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GitLens
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Githru Insights
Discover top contributors by file, branch, or PR area to route reviews and clarify ownership. Assess pull requests with impact metrics to surface risky changes and long-tail hotspots. Visualize repository storylines and author work patterns to plan refactors and improve collaboration.
Githru Insights v0.1
# Githru MCP Server <p align="center"> <strong>A powerful Model Context Protocol (MCP) server that provides advanced Git repository analysis and visualization tools designed to enhance team collaboration.</strong> </p> --- ## 🚀 Overview The **Githru MCP Server** extends Claude’s capabilities
OSS Insight
Unleash GitHub data insights with AI-powered SQL and real-time...
Best For
- ✓open-source project maintainers documenting project growth
- ✓developers creating portfolio visualizations
- ✓teams analyzing competitive GitHub project metrics
- ✓technical writers embedding project statistics in documentation
- ✓competitive analysis and market research
- ✓ecosystem maintainers tracking related projects
- ✓investors evaluating open-source project portfolios
- ✓technical teams benchmarking tool adoption
Known Limitations
- ⚠SVG output only — no JSON/structured data export for programmatic analysis
- ⚠Limited to public GitHub repositories — private repositories not supported
- ⚠Historical data accuracy depends on GitHub API availability at time of data collection
- ⚠No real-time updates — chart reflects data at generation time, not live star counts
- ⚠Single repository or multi-repo visualization limited by URL parameter length constraints
- ⚠No timezone customization — dates rendered in UTC or server timezone
Requirements
Input / Output
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