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MCP Git Server

Anthropic

80·Strong

Overall Trust Score

Official Anthropic MCP server for Git repository operations. Enables AI models to interact with local Git repositories, perform commits, branch management, and version control operations. Essential for AI-assisted development workflows and code management.

git
version-control
mcp
model-context-protocol
Version: 2025.9.25
Last Evaluated: November 9, 2025
Official Website →

Trust Vector

Performance & Reliability

87
git operation success rate
90
Methodology
Operation success testing
Evidence
MCP Git Server
Reliable Git operations using native Git CLI or libraries
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
repository parsing accuracy
88
Methodology
Parsing accuracy assessment
Evidence
Git Implementation
Uses standard Git tools for accurate repository analysis
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
large repository handling
82
Methodology
Scalability testing
Evidence
Implementation Review
Performance may degrade with very large repositories (>100k commits)
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
merge conflict handling
85
Methodology
Conflict handling testing
Evidence
Git Conflict Resolution
Properly detects and reports merge conflicts for manual resolution
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
error recovery
89
Methodology
Error handling testing
Evidence
MCP Implementation
Graceful error handling with detailed error messages
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09

Security

70
repository access control
75
Methodology
Access control testing
Evidence
File System Permissions
Respects local file system permissions but AI can access any readable repo
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
destructive operation risk
62
Methodology
Operation authorization testing
Evidence
Security Analysis
AI can perform force pushes, branch deletions, and history rewrites
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
credential exposure risk
68
Methodology
Credential security analysis
Evidence
Git Credential Storage
Uses local Git credentials; potential for accidental exposure to LLM
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
commit signing support
78
Methodology
Signing capability review
Evidence
Git Commit Signing
Supports GPG signing if configured in local Git setup
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
branch protection respect
70
Methodology
Protection mechanism testing
Evidence
Implementation Review
Local operations only; remote branch protections enforced by remote server
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Privacy & Compliance

66
code exposure
62
Methodology
Data flow analysis
Evidence
MCP Data Flow
Repository content and commit history sent to LLM provider
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
sensitive data detection
60
Methodology
Privacy controls assessment
Evidence
Security Analysis
No built-in secret detection; risk of exposing API keys in commits
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
commit history privacy
68
Methodology
History privacy review
Evidence
Git Log Access
Full commit history including author names and emails accessible
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
third party data sharing
70
Methodology
Data sharing analysis
Evidence
LLM Provider Policies
Repository data shared with LLM provider per their privacy policy
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
gitignore respect
72
Methodology
File filtering assessment
Evidence
Implementation Review
Respects .gitignore for operations but can still read ignored files
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Trust & Transparency

90
documentation quality
93
Methodology
Documentation completeness review
Evidence
MCP Git Docs
Comprehensive documentation with examples and best practices
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
operation visibility
92
Methodology
Logging and traceability assessment
Evidence
Git and MCP Logging
All operations logged in MCP and Git reflog provides full audit trail
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
open source transparency
95
Methodology
Source code review
Evidence
GitHub Repository
Fully open source implementation with MIT license
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command coverage clarity
82
Methodology
API documentation review
Evidence
MCP Server Documentation
Clear documentation of supported Git commands and operations
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Operational Excellence

88
ease of setup
92
Methodology
Setup complexity assessment
Evidence
MCP Setup Guide
Simple setup requiring only Git installation on local system
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
operation performance
85
Methodology
Performance benchmarking
Evidence
Git Performance
Fast operations for most repos; performance depends on repository size
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
reliability
90
Methodology
Stability analysis
Evidence
Git Stability
Built on mature, battle-tested Git tooling
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
feature coverage
87
Methodology
Feature completeness assessment
Evidence
MCP Git Server
Covers commits, branches, logs, diffs, and most common Git operations
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
community adoption
85
Methodology
Community activity analysis
Evidence
GitHub Community
Popular MCP server for development workflows
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

✨ Strengths

  • •Comprehensive Git operation support (commits, branches, merges, logs)
  • •Built on mature and reliable Git infrastructure
  • •Excellent for development workflows and version control automation
  • •Full operation auditability through Git reflog and MCP logs
  • •Open source implementation with active Anthropic support
  • •Simple setup requiring only local Git installation

⚠️ Limitations

  • •Repository code and history exposed to LLM provider APIs
  • •Risk of destructive operations (force push, branch deletion, history rewrite)
  • •No built-in secret detection or sensitive data filtering
  • •Can access Git credentials stored on local system
  • •Performance may degrade with very large repositories
  • •No safeguards against accidental commits or pushes

📊 Metadata

license: MIT
supported platforms:
0: All platforms with Git installed
programming languages:
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers
github stars: 58700
api dependency: Git CLI
authentication: Uses local Git credentials
first release: 2024-11
maintained by: Anthropic
status: Official - Active
transport types:
0: stdio
installation methods:
0: npm

Use Case Ratings

code generation

95

Excellent for AI-assisted development with version control integration

customer support

65

Limited applicability; mainly useful for technical support on code repositories

content creation

75

Good for managing documentation and content versioning in Git

data analysis

78

Useful for analyzing commit history, code churn, and repository metrics

research assistant

82

Great for researching code history, finding changes, and tracking evolution

legal compliance

60

Risk of exposing proprietary code; requires careful access controls

healthcare

55

Low suitability due to risk of exposing sensitive healthcare code

financial analysis

63

Moderate risk; requires careful repository access controls

education

90

Excellent for teaching Git, version control, and collaborative development

creative writing

78

Good for version controlling writing projects and tracking revisions