"Git" matching MCP servers:

for tokenectomy git workflow

An autonomous GitHub management engine that enables control over repositories, branches, security alerts, and Actions workflows through natural language. It utilizes a zero-local-footprint architecture by storing all configuration and audit logs within a private state repository on GitHub.

An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.

Reduces token waste by caching code understanding in .mi context files and prevents agent conflicts by coordinating intent and file access across sessions.

Manages isolated Git worktrees for each ZCode thread, enabling safe parallel development with automatic setup, snapshot-based removal, PR review, and background agent orchestration.

Analyzes git changes in repositories and generates conventional commit messages using OpenAI's GPT models, supporting both staged and unstaged changes with detailed summaries.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

A filesystem-based MCP server for AI coding agents to coordinate work across git worktrees by claiming files, checking for conflicts, and logging progress without affecting the repository's git history.

Enables autonomous triage of GitHub issues and pull requests through MCP, with classification, deduplication, prioritization, and safe human-in-the-loop actions.

Exposes GitHub issue and pull-request triage capabilities to any MCP client: fetching repository context, classifying and prioritizing requests, finding duplicates, and applying labels, comments, assignments, closures, or reopenings. All writes are policy-gated, dry-run by default, and destructive actions require explicit two-step human confirmation.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A MCP server that bridges LLMs with GitHub repository management, enabling automated analysis of pull requests, issue management, tag creation, and release management through natural language.

Provides a Model Context Protocol interface for secure, multi-agent collaboration on Git repositories, offering isolated workspaces, change requests, reviews, and approval workflows with Git as the source of truth.

Enables AI agents to query live, human-approved rules before taking actions, ensuring compliance and reducing errors.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project-management layer, handling task checkout, atomic claims, heartbeats, reviews, token budgets, and AI-powered PRD, sprint, triage, and roadmap workflows. It also provides GitHub Actions, Releases, Branches, MCP Resources, and MCP Prompts support with GitHub-native storage.

Enables coordinating Claude Code and Codex across separate Git worktrees with shared issue ownership, file reservations, messages, and explicit handoffs.

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.

Enables AI coding agents and human managers to coordinate work on GitHub Projects v2 through 20 tools and 169 actions for autonomous task checkout, heartbeats, reviews, token budgets, PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines, backed by GitHub-native storage and MCP resources/prompts.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Provides MCP tools that give AI agents persistent, append-only memory in a git repository, letting them record observations, decisions, and corrections while retrieving context briefs, current facts, conflicts, and traceable event history without a vector database.