"A platform for managing software development and version control" matching MCP servers:

Enables AI agents to manage version control for product assets with tools for creating change sets, comparing versions, approving merges, and exporting receipts.

An MCP server for managing Maven dependency versions using direct metadata parsing from Maven Central. It provides tools to fetch latest stable versions, list version history, and compare versions with upgrade recommendations.

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

Enables managing technical specifications with version control, search, and comparison features, deployed as a secure Auth0-authenticated Cloudflare Worker.

Centralized MCP server that provides standardized development workflow commands to Cursor AI, auto-detecting project type (Laravel, Next.js, Flutter, Architecture) and offering relevant commands for implementation, testing, and commits.

A version management server for MCP skills that enables automated update detection, parallel version testing, and smart merging of custom modifications with official updates. It allows users to safely switch, rollback, and manage local skill versions through a standardized suite of MCP tools.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

A production-ready MCP server for triaging and reviewing GitHub pull requests via the GitHub REST API, providing typed tools to list, inspect, comment, add labels, and submit reviews.

Enables users to safely read, write, edit, create directories, and list trees within a structured local Windows environment, with strict path validation and Git-based undo/version control.

Enables AI agents and MCP clients to compute real-time, in-memory unified diffs between versions of live artifacts along with structured change telemetry. It runs as a deterministic, zero-dependency Python MCP server that plugs into Claude Desktop, Cursor, or Windsurf for diff and change-tracking workflows.

A Model Context Protocol server that enables Claude to manage software development projects with complete context awareness and code execution through Docker environments.

Enables developers and AI agents to compute deterministic in-memory unified diffs between successive versions of live artifacts and receive structured change telemetry in return. It runs with zero external dependencies and plugs into MCP-compliant clients such as Claude Desktop, Cursor, and Windsurf.

Enables Codex and other MCP clients to read kickoff cards, acceptance criteria, Git evidence, and next steps, then append validated, audited progress events for resumable project handoffs.

Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.

Self-hosted MCP coding server and unified local Control Center for ChatGPT web, enabling file editing, command execution, Git operations, and optional upstream MCP tools with conversation access controls.

It enables AI agents to retrieve Git-backed project context, handoff packages, and next actions, then append validated, audited progress events as project-record commits.

It lets AI coding clients read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a validated, audited, idempotent progress event with a matching project-record Git commit.

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events with a matching Git commit.

An MCP server that enforces development discipline and workflow best practices, guiding users through a structured process of coding, testing, documenting, committing, and releasing.

Enables AI agents and humans to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step, then append audited, idempotent progress events that are committed to the project's Git record. Access is scoped per project through short-lived, revocable credentials, keeping high-risk actions outside the tool surface for human approval.