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MCP Filesystem Server

Anthropic

81·Strong

Overall Trust Score

Official MCP server providing AI models with controlled access to the local filesystem. Enables file reading, writing, and directory operations through the Model Context Protocol. Critical for file-based workflows but requires careful security configuration.

file-system
local
mcp
model-context-protocol
Version: 2025.7.1
Last Evaluated: November 9, 2025
Official Website →

Trust Vector

Performance & Reliability

91
file operation accuracy
94
Methodology
File operation testing across multiple platforms
Evidence
MCP Documentation
Direct filesystem operations with high accuracy and reliability
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
response time
95
Methodology
Latency benchmarking
Evidence
MCP Performance Testing
Local filesystem operations complete in milliseconds
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
error handling
90
Methodology
Error scenario testing
Evidence
MCP Server Implementation
Comprehensive error handling for permissions, disk space, and invalid paths
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
cross platform compatibility
88
Methodology
Multi-platform testing
Evidence
MCP GitHub Repository
Supports Windows, macOS, and Linux with platform-specific path handling
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
large file handling
87
Methodology
Large file performance testing
Evidence
Community Testing
Handles large files efficiently with streaming support
Date: 2024-10-20
Confidence: mediumLast verified: 2025-11-09

Security

68
access control
72
Methodology
Access control testing
Evidence
MCP Security Documentation
Requires explicit directory allowlist configuration, but enforcement depends on setup
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
path traversal protection
75
Methodology
Path traversal attack testing
Evidence
MCP Server Code
Built-in path normalization prevents basic traversal attacks
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
permission enforcement
65
Methodology
Permission boundary testing
Evidence
Security Analysis
Relies on OS-level permissions; AI can request any file within allowed directories
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
audit logging
70
Methodology
Logging capabilities review
Evidence
MCP Logging
Basic operation logging available, detailed audit logs require custom implementation
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
data exfiltration risk
60
Methodology
Data flow analysis
Evidence
Security Review
AI models have read access to all allowed directories; sensitive data exposure risk
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09

Privacy & Compliance

72
data exposure control
68
Methodology
Data flow analysis
Evidence
MCP Architecture
File contents sent to LLM provider; requires careful directory scope configuration
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
pii protection
65
Methodology
Privacy features assessment
Evidence
MCP Security Guidelines
No built-in PII detection or redaction; responsibility on developer
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
local processing
85
Methodology
Data processing architecture review
Evidence
MCP Architecture
Server runs locally, but file content is transmitted to LLM API
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
gdpr compliance
70
Methodology
Compliance framework review
Evidence
MCP Documentation
GDPR compliance depends on LLM provider and user configuration
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Trust & Transparency

85
documentation quality
90
Methodology
Documentation completeness review
Evidence
MCP Docs
Comprehensive documentation with clear setup instructions and examples
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
operation visibility
82
Methodology
Logging capabilities assessment
Evidence
MCP Protocol
All filesystem operations visible in MCP message logs
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
open source code
95
Methodology
Source code review
Evidence
GitHub Repository
Fully open source with MIT license, code auditable
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
security guidance
78
Methodology
Security documentation review
Evidence
MCP Security Docs
Provides security best practices but could be more comprehensive
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Operational Excellence

88
ease of setup
90
Methodology
Setup complexity assessment
Evidence
MCP Quickstart
Simple npm/pip installation with minimal configuration
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
resource efficiency
92
Methodology
Resource utilization testing
Evidence
Performance Testing
Minimal CPU and memory overhead for file operations
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
stability
88
Methodology
Issue tracking analysis
Evidence
Community Reports
Stable operation with few reported bugs
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
maintenance requirements
85
Methodology
Maintenance overhead assessment
Evidence
MCP Server Updates
Regular updates from Anthropic, minimal maintenance required
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
community support
82
Methodology
Community activity analysis
Evidence
GitHub Discussions
Growing community support, relatively new protocol (late 2024)
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

✨ Strengths

  • •Fast, local file operations with minimal latency
  • •Cross-platform support (Windows, macOS, Linux)
  • •Simple setup and configuration
  • •Open source and fully auditable code
  • •Comprehensive documentation from Anthropic
  • •Efficient handling of large files with streaming support

⚠️ Limitations

  • •Significant security risk if misconfigured - AI can access all allowed files
  • •No built-in PII or sensitive data detection/redaction
  • •File contents sent to external LLM provider APIs
  • •Limited granular permission controls beyond directory allowlists
  • •Potential for accidental data exfiltration to LLM providers
  • •Audit logging requires custom implementation for compliance needs

📊 Metadata

license: MIT
supported platforms:
0: Windows
1: macOS
2: Linux
programming languages:
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers
github stars: 58700
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 code generation workflows requiring file reading and writing

customer support

65

Limited utility for customer support; mainly for loading reference documents

content creation

88

Good for content workflows involving file-based templates and outputs

data analysis

82

Useful for loading data files, but limited analysis capabilities

research assistant

90

Excellent for accessing research papers, documents, and notes

legal compliance

70

Useful for document access but requires strict security controls

healthcare

60

High risk due to PHI exposure; requires careful configuration and HIPAA controls

financial analysis

68

Risky for sensitive financial data; requires strict directory restrictions

education

85

Good for accessing educational materials and student work

creative writing

92

Excellent for managing drafts, outlines, and creative project files