MCP Time Server
Anthropic
92·Exceptional
Overall Trust Score
Official Anthropic MCP server for time and timezone operations. Provides AI models with current time information, timezone conversions, date calculations, and scheduling assistance. Essential for time-sensitive workflows and international collaboration.
time
utilities
mcp
model-context-protocol
Trust Vector
Performance & Reliability
92
time accuracy95
time accuracy
95
Methodology
Time accuracy verification
Evidence
Confidence: highLast verified: 2025-11-09
timezone conversion accuracy93
timezone conversion accuracy
93
Methodology
Conversion accuracy testing
Evidence
Confidence: highLast verified: 2025-11-09
dst handling90
dst handling
90
Methodology
DST edge case testing
Evidence
Confidence: highLast verified: 2025-11-09
date calculation reliability91
date calculation reliability
91
Methodology
Date calculation testing
Evidence
Confidence: highLast verified: 2025-11-09
response speed95
response speed
95
Methodology
Performance benchmarking
Evidence
Confidence: highLast verified: 2025-11-09
Security
95
read only operations98
read only operations
98
Methodology
Operation authorization review
Evidence
Confidence: highLast verified: 2025-11-09
system time manipulation risk100
system time manipulation risk
100
Methodology
System modification testing
Evidence
Implementation Review
Cannot modify system time; read-only access to time information
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
data exposure risk92
data exposure risk
92
Methodology
Data flow security analysis
Evidence
Confidence: highLast verified: 2025-11-09
timezone inference privacy90
timezone inference privacy
90
Methodology
Privacy impact assessment
Evidence
Confidence: mediumLast verified: 2025-11-09
resource consumption95
resource consumption
95
Methodology
Resource consumption testing
Evidence
Confidence: highLast verified: 2025-11-09
Privacy & Compliance
88
location inference risk85
location inference risk
85
Methodology
Location privacy assessment
Evidence
Confidence: mediumLast verified: 2025-11-09
temporal pattern exposure88
temporal pattern exposure
88
Methodology
Pattern analysis
Evidence
Confidence: lowLast verified: 2025-11-09
data minimization92
data minimization
92
Methodology
Data minimization review
Evidence
Confidence: highLast verified: 2025-11-09
third party data sharing88
third party data sharing
88
Methodology
Data sharing analysis
Evidence
Confidence: highLast verified: 2025-11-09
Trust & Transparency
91
documentation quality90
documentation quality
90
Methodology
Documentation completeness review
Evidence
Confidence: highLast verified: 2025-11-09
operation visibility92
operation visibility
92
Methodology
Logging and traceability assessment
Evidence
Confidence: highLast verified: 2025-11-09
open source transparency95
open source transparency
95
Methodology
Source code review
Evidence
Confidence: highLast verified: 2025-11-09
timezone data source clarity88
timezone data source clarity
88
Methodology
Data source transparency review
Evidence
Confidence: highLast verified: 2025-11-09
Operational Excellence
93
ease of setup95
ease of setup
95
Methodology
Setup complexity assessment
Evidence
Confidence: highLast verified: 2025-11-09
operation performance95
operation performance
95
Methodology
Performance benchmarking
Evidence
Confidence: highLast verified: 2025-11-09
reliability95
reliability
95
Methodology
Reliability testing
Evidence
Confidence: highLast verified: 2025-11-09
feature coverage90
feature coverage
90
Methodology
Feature completeness assessment
Evidence
Confidence: highLast verified: 2025-11-09
community adoption90
community adoption
90
Methodology
Community activity analysis
Evidence
Confidence: mediumLast verified: 2025-11-09
✨ Strengths
- •Highly accurate time and timezone information from authoritative sources
- •Zero-configuration setup with no external dependencies
- •Read-only operations eliminate security and modification risks
- •Near-instantaneous performance with minimal resource usage
- •Open source with comprehensive documentation
- •Proper handling of complex timezone and DST scenarios
⚠️ Limitations
- •System timezone may reveal general user location
- •Limited to time information; no calendar or scheduling features
- •Cannot modify system time (by design)
- •Query patterns may reveal user schedule to LLM provider
- •Depends on system time accuracy and timezone database updates
- •No advanced scheduling or reminder capabilities
📊 Metadata
license: MIT
supported platforms:
0: All platforms with Node.js/Python
programming languages:
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers
github stars: 58700
api dependency: System time APIs, IANA Time Zone Database
authentication: None required
first release: 2024-11
maintained by: Anthropic
status: Official - Active
transport types:
0: stdio
installation methods:
0: npm
1: pip
Use Case Ratings
code generation
85
Useful for timestamp generation and time-based logic implementation
customer support
88
Excellent for scheduling, business hours calculation, and timezone coordination
content creation
80
Good for content scheduling and publication timing
data analysis
82
Useful for temporal data analysis and time-series calculations
research assistant
75
Helpful for research scheduling and deadline management
legal compliance
78
Useful for compliance deadline tracking and document timestamping
healthcare
80
Good for appointment scheduling and medication timing
financial analysis
85
Important for market hours, trading windows, and settlement timing
education
88
Excellent for class scheduling and assignment deadline management
creative writing
70
Useful for story timelines and publication scheduling