GitHub Stars
This MCP server provides GitHub stars analysis and timeline tracking capabilities through the GitHub GraphQL API, enabling AI assistants to retrieve user starred repositories, analyze starring patterns over time, and extract technology adoption insights. Built using FastMCP 2.2.0+ with Python 3.11+, it offers tools for fetching starred repositories with pagination support, timeline analysis with monthly activity breakdowns, language distribution analysis, and repository ranking by popularity. The implementation features async/await patterns for performance, TTL caching for API response optimization, structured logging with structlog, robust error handling for GitHub API rate limits and authentication failures, and comprehensive data models using Pydantic for validation, making it valuable for developer research workflows, technology trend analysis, and building AI assistants that need programmatic access to GitHub starring behavior without manual repository browsing.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- version-control
- Source
- PulseMCP
- Repository
- github.com/dustyposa/github-stars-mcp-server
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve GitHub Stars from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.