Top 10 MCP Servers for Git Tools (2026)

Top 10 MCP Servers for Git Tools (2026)

The Model Context Protocol (MCP) has changed how AI assistants interact with developer tools. Instead of pasting git diffs into chat windows or describing repository structures manually, MCP servers let AI models read, search, and manipulate git repositories directly.

This guide covers the 10 best MCP servers for git-related operations, from managing GitHub pull requests to searching commit history and automating code reviews.

What Is MCP?

MCP (Model Context Protocol) is an open standard created by Anthropic that provides a universal way for AI models to connect to external tools and data sources. An MCP server exposes specific capabilities (called "tools") that any MCP-compatible client can use.

For git workflows, MCP servers can:

• Read and search repository contents
• Create and manage branches, commits, and pull requests
• Run code reviews and analyze diffs
• Search issues and discussions
• Manage releases and deployments

MCP Clients That Support Git Servers

Client	Platform	MCP Support
Claude Desktop	macOS, Windows	Full
Claude Code	CLI (all platforms)	Full
Cursor	macOS, Windows, Linux	Full
VS Code (Continue)	All platforms	Full
Windsurf	macOS, Windows, Linux	Full
Zed	macOS, Linux	Partial

1. GitHub Official MCP Server

Best for: Full GitHub integration

The official GitHub MCP server, maintained by GitHub, provides comprehensive access to the GitHub API through MCP.

Key Features

• Create and manage repositories, branches, and pull requests
• Search code, issues, and discussions across repositories
• Read file contents and directory structures
• Manage issues, labels, and milestones
• Access GitHub Actions workflow status

Setup

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_your_token_here"
      }
    }
  }
}

Available Tools

Tool	Description
search_repositories	Search GitHub repositories
get_file_contents	Read file or directory contents
create_or_update_file	Create or update a file
push_files	Push multiple files in one commit
create_issue	Create a new issue
create_pull_request	Create a pull request
search_code	Search code across repositories
list_commits	List recent commits
get_pull_request_diff	Get the diff of a PR

GitHub: github.com/modelcontextprotocol/servers

2. GitLab MCP Server

Best for: GitLab-hosted repositories

Provides similar functionality to the GitHub MCP server but for GitLab instances, including self-hosted GitLab installations.

Key Features

• Full GitLab API access through MCP
• Support for self-hosted GitLab instances
• Merge request management
• CI/CD pipeline status
• Issue and milestone tracking

Setup

{
  "mcpServers": {
    "gitlab": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-gitlab"],
      "env": {
        "GITLAB_PERSONAL_ACCESS_TOKEN": "glpat-your_token_here",
        "GITLAB_API_URL": "https://gitlab.com/api/v4"
      }
    }
  }
}

For self-hosted GitLab, change GITLAB_API_URL to your instance URL.

3. Git Local MCP Server

Best for: Working with local repositories without pushing to remote

This server operates directly on local git repositories, providing AI assistants with access to git operations without requiring a GitHub or GitLab account.

Key Features

• Read git log, diff, and status
• Create branches and commits
• Search commit messages and file history
• View blame information
• Stage and unstage files

Setup

{
  "mcpServers": {
    "git": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-git"],
      "env": {}
    }
  }
}

Available Tools

Tool	Description
git_log	View commit history
git_diff	Show changes between commits or working tree
git_status	Show working tree status
git_show	Show details of a specific commit
git_blame	Show line-by-line authorship
git_branch	List or create branches
git_checkout	Switch branches
git_commit	Create a commit

4. Linear MCP Server

Best for: Connecting git workflows to Linear issue tracking

Linear is a popular project management tool for engineering teams. This MCP server bridges Linear issues with git workflows.

Key Features

• Search and create Linear issues from AI conversations
• Link commits and PRs to Linear issues
• Update issue status based on git operations
• View project backlogs and sprints

Setup

{
  "mcpServers": {
    "linear": {
      "command": "npx",
      "args": ["-y", "mcp-linear"],
      "env": {
        "LINEAR_API_KEY": "lin_api_your_key_here"
      }
    }
  }
}

5. GitHub Code Review MCP Server

Best for: AI-powered pull request reviews

A specialized MCP server focused on code review workflows. It gives AI assistants the context they need to provide meaningful code review feedback.

Key Features

• Fetch PR diffs with full file context
• Access PR comments and review threads
• Understand CI/CD check results
• Post review comments inline on specific lines
• Suggest code changes in review format

Example Workflow

With this server configured, you can ask your AI assistant:

Review PR #42 on the main-api repository. Focus on security
issues and suggest improvements to error handling.

The AI can read the entire diff, understand the context from surrounding code, check CI results, and post line-by-line comments.

6. Sentry MCP Server

Best for: Connecting error tracking to git workflows

Links Sentry error monitoring with your git repositories so AI assistants can correlate errors with recent commits.

Key Features

• Search Sentry issues and events
• Correlate errors with specific commits
• Access stack traces and error context
• Link Sentry issues to GitHub/GitLab issues

Setup

{
  "mcpServers": {
    "sentry": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sentry"],
      "env": {
        "SENTRY_AUTH_TOKEN": "your_sentry_token",
        "SENTRY_ORG": "your-org-slug"
      }
    }
  }
}

7. Jira MCP Server

Best for: Enterprise teams using Jira for project management

Connects Jira issue tracking with AI-assisted git workflows.

Key Features

• Search and create Jira issues
• Update issue status and fields
• Link issues to branches and pull requests
• View sprint boards and backlogs
• Add comments and attachments

Setup

{
  "mcpServers": {
    "jira": {
      "command": "npx",
      "args": ["-y", "mcp-jira"],
      "env": {
        "JIRA_URL": "https://your-org.atlassian.net",
        "JIRA_EMAIL": "your@email.com",
        "JIRA_API_TOKEN": "your_jira_api_token"
      }
    }
  }
}

8. Sourcegraph MCP Server

Best for: Code search across multiple repositories

Sourcegraph provides powerful code search across your entire codebase, including multiple repositories. The MCP server makes this available to AI assistants.

Key Features

• Search code across all connected repositories
• Regex and structural search support
• Find references and definitions
• Navigate cross-repository dependencies
• Search commit diffs and messages

Setup

{
  "mcpServers": {
    "sourcegraph": {
      "command": "npx",
      "args": ["-y", "mcp-sourcegraph"],
      "env": {
        "SOURCEGRAPH_ENDPOINT": "https://sourcegraph.com",
        "SOURCEGRAPH_ACCESS_TOKEN": "sgp_your_token"
      }
    }
  }
}

9. Docker MCP Server

Best for: Managing containerized development environments alongside git

While not strictly a git tool, Docker is deeply intertwined with modern git workflows. This MCP server lets AI assistants manage containers that are part of your development pipeline.

Key Features

• Build and manage Docker images
• Start, stop, and inspect containers
• Read container logs
• Manage docker-compose services
• Debug failing CI/CD builds that use Docker

Setup

{
  "mcpServers": {
    "docker": {
      "command": "npx",
      "args": ["-y", "mcp-docker"]
    }
  }
}

10. Filesystem MCP Server

Best for: Reading and navigating project files alongside git operations

The filesystem MCP server provides read/write access to your local files, which complements git MCP servers by giving AI assistants the ability to read, search, and modify code files.

Key Features

• Read and write files
• Search file contents
• List directory structures
• Create and move files
• Works alongside git MCP servers for a complete workflow

Setup

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/your/project"
      ]
    }
  }
}

Comparison Table

MCP Server	Platform	Auth Required	Best Feature
GitHub Official	GitHub	PAT token	Full GitHub API access
GitLab	GitLab (cloud + self-hosted)	PAT token	Self-hosted support
Git Local	Local repos	None	No remote needed
Linear	Linear	API key	Issue-to-code linking
GitHub Code Review	GitHub	PAT token	Inline review comments
Sentry	Sentry	Auth token	Error-to-commit correlation
Jira	Jira/Atlassian	API token	Enterprise project mgmt
Sourcegraph	Multi-repo	Access token	Cross-repo code search
Docker	Local Docker	None	Container management
Filesystem	Local files	None	File read/write access

How to Configure Multiple MCP Servers

You can run multiple MCP servers simultaneously. Here is an example Claude Desktop configuration that combines several:

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxx"
      }
    },
    "git": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-git"]
    },
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/you/projects"]
    }
  }
}

This gives your AI assistant the ability to search GitHub, operate on local git repos, and read project files, all in a single conversation.

Wrapping Up

MCP servers are transforming how developers interact with git through AI assistants. Start with the GitHub or GitLab official server for remote repository management, add the local git server for day-to-day development, and layer in specialized servers like Sentry or Linear based on your team's toolchain.

If you are building AI-powered developer tools or applications that generate visual content from code, check out Hypereal AI. Hypereal provides APIs for AI image generation, video creation, and other media tasks that integrate smoothly into modern development workflows.