"Information about Git, a version control system" matching MCP servers:

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Gives coding agents the exact installed version of each dependency in a project from node_modules and lockfile, preventing deprecated API usage by grounding them in reality.

Provides up-to-date AI model names and pricing from models.dev, solving model hallucination by fetching recently released models.

Enables local-first document versioning with content-addressable storage, word-level AST diffs, and AI-compliance auditing for LLM agents.

Enables system automation and control including command execution, process management, network tools, environment variables, disk usage, and service status.

Enables AI agents to intelligently organize Git changes into clean, focused commits with autopilot mode or surgical line-by-line staging precision. Supports partial staging of untracked files and handles large diffs with smart truncation.

A deterministic MCP server that reimplements ai-git-fish workflows (aicommit, aibranch, aipr) with Leantime integration, enabling Claude Code and Codex to perform git operations and manage tickets without an internal LLM.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

A local MCP server that provides a safe, explicit set of Git operations for version control tasks like status, diff, branching, staging, committing, fetching, merging, and pushing.

Deterministic, LLM-first control of Word documents (.docx). An agent reads the outline, finds text by phrase, and applies edits as tracked changes and comments in one atomic batch, with a safety layer that refuses edits based on a stale read and rolls back failed batches. It works on .docx files directly, and can also drive an open document in Microsoft Word on Windows or in LibreOffice Writer.

Enables AI coding agents to retrieve the latest stable versions of packages and tools across multiple ecosystems, preventing outdated dependency versions in generated code.

Enables local, timestamped search over GitHub Awesome channel featured repositories with SQLite/FTS5 catalog, offering tools to search repos, get repo details, check catalog status, and update from video data.

Enables generating conventional-commit–grouped release notes and CHANGELOG.md drafts from a local repository's git log between tags or commits, plus grouping commits by type. Reads only local git history via an MCP client such as Cursor or Claude Desktop.

Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.

A secure, read-only MCP server for AI-powered system monitoring. It provides real-time OS metrics, config discovery, and safe log tailing to enable autonomous infrastructure audits without shell access risks.

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.

An open-source MCP server that gives parents real-time oversight and guardrails over their children's AI agent interactions, with features like content filtering, spiral detection, and approval flows.