GitInsight-MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GITHUB_TOKEN | Yes | GitHub Personal Access Token. Generate at: https://github.com/settings/tokens. Required scopes: repo, read:user, read:org | |
| GITHUB_USERNAME | Yes | Your GitHub username | |
| CACHE_TTL_SECONDS | No | Cache time-to-live in seconds | 3600 |
| CACHE_CHECK_PERIOD_SECONDS | No | Cache check period in seconds | 600 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_repositoriesB | Lists all public repositories for GitHub user: octocat. Returns repository metadata including name, description, stars, forks, language, topics, and last update date. Supports sorting by stars, forks, updated date, or name. Optionally limit the number of results. |
| get_repository_detailsA | Gets detailed information about a specific repository including full metadata, topics, README content, open issues count, creation date, and homepage URL. Useful for deep-diving into a particular project. |
| get_recent_commitsA | Fetches recent commits either for a specific repository or across all repositories. Returns commit SHA, message, author, date, and URL. Useful for tracking recent development activity. |
| get_repository_statsA | Calculates aggregate statistics across all repositories including: total repositories count, total stars, total forks, language breakdown with percentages, most starred/forked repositories, recently updated repos, and total open issues. Perfect for portfolio summaries and analytics. |
| search_projects_by_techA | Searches and filters repositories by technology stack, programming language, topics, or minimum stars. Supports advanced filtering and sorting. Use this to find projects by category (e.g., "all Python projects", "DevOps projects", "AI/ML repositories"). |
| get_contribution_activityB | Analyzes contribution activity and returns metrics including: total commits, repositories contributed to, most active day, and contribution streak. Useful for understanding development patterns and activity trends. |
| get_skills_matrixA | 🎯 RECRUITER TOOL: Generates a comprehensive skills matrix analyzing all repositories. Returns categorized technical skills (Programming Languages, DevOps, Cloud), proficiency levels, domain expertise (Web Dev, AI/ML, DevOps), and project counts. Perfect for HR screening and technical assessment. |
| generate_portfolio_summaryB | 📄 RECRUITER TOOL: Creates a recruiter-friendly portfolio summary with candidate profile, professional summary, key achievements, featured projects with highlights, technical proficiency breakdown, and GitHub metrics. Optimized for HR review and candidate evaluation. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| recruiter_evaluation | 🎯 HR Tool: Comprehensive candidate evaluation for recruiters |
| technical_assessment | 🔧 Technical deep-dive for engineering managers |
| portfolio_showcase | 💼 Generate an impressive portfolio presentation |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Developer Profile | Complete developer profile with contact info and expertise areas |
| Professional Resume | Markdown-formatted resume/CV generated from GitHub data |
| Skills Matrix | Comprehensive technical skills assessment with proficiency levels |
TDQS
Scored across 8 tools
Most tools have distinct purposes, but there is some overlap between get_repository_stats and get_contribution_activity, as both provide aggregated metrics that could be confused for general analytics. The recruiter-focused tools (generate_portfolio_summary and get_skills_matrix) are clearly differentiated from data-fetching tools, but the boundary between statistical and activity analysis tools is slightly blurred.
All tool names follow a consistent verb_noun pattern (e.g., generate_portfolio_summary, get_contribution_activity, list_repositories), using snake_case throughout. The naming is predictable and readable, with no deviations in style or convention across the set.
With 8 tools, the count is well-scoped for a GitHub analytics server, covering key areas like repository listing, details, stats, activity, skills analysis, and project search. Each tool serves a specific function without redundancy, making the set manageable and purposeful.
The toolset provides comprehensive coverage for GitHub portfolio and analytics, including data retrieval (repositories, commits, details), statistical analysis, skills assessment, and project filtering. A minor gap is the lack of tools for modifying or interacting with GitHub (e.g., creating issues or pull requests), but this aligns with the server's focus on insight rather than action.