MCP Gmail Server
Community
75·Strong
Overall Trust Score
Community-maintained MCP server for Gmail email operations. Enables AI models to read, send, search, label, and manage emails through the Gmail API. Includes support for attachments, threading, and advanced search. Essential for AI-powered email automation and communication workflows.
email
google
mcp
model-context-protocol
Trust Vector
Performance & Reliability
83
email search accuracy88
email search accuracy
88
Methodology
Search accuracy testing
Evidence
Confidence: highLast verified: 2025-11-09
send reliability85
send reliability
85
Methodology
Send success rate testing
Evidence
Confidence: highLast verified: 2025-11-09
rate limit handling78
rate limit handling
78
Methodology
Rate limiting behavior testing
Evidence
Confidence: mediumLast verified: 2025-11-09
attachment handling82
attachment handling
82
Methodology
Attachment processing testing
Evidence
Confidence: mediumLast verified: 2025-11-09
error recovery80
error recovery
80
Methodology
Error handling testing
Evidence
Confidence: mediumLast verified: 2025-11-09
Security
70
authentication security82
authentication security
82
Methodology
Authentication mechanism review
Evidence
Confidence: highLast verified: 2025-11-09
token exposure risk65
token exposure risk
65
Methodology
Token security analysis
Evidence
Confidence: highLast verified: 2025-11-09
email send risk60
email send risk
60
Methodology
Operation authorization testing
Evidence
Confidence: highLast verified: 2025-11-09
email deletion risk68
email deletion risk
68
Methodology
Destructive operation testing
Evidence
Confidence: highLast verified: 2025-11-09
scope limitation75
scope limitation
75
Methodology
Permission scope testing
Evidence
Confidence: mediumLast verified: 2025-11-09
audit logging78
audit logging
78
Methodology
Audit logging review
Evidence
Google Workspace Audit
Operations logged in Google Workspace audit logs (for Workspace accounts)
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
Privacy & Compliance
64
email content exposure58
email content exposure
58
Methodology
Data flow analysis
Evidence
Confidence: highLast verified: 2025-11-09
contact information exposure62
contact information exposure
62
Methodology
PII exposure assessment
Evidence
Confidence: highLast verified: 2025-11-09
attachment privacy60
attachment privacy
60
Methodology
Attachment privacy assessment
Evidence
Confidence: highLast verified: 2025-11-09
third party data sharing68
third party data sharing
68
Methodology
Data sharing analysis
Evidence
LLM Provider Policies
Email content shared with LLM provider per their privacy policy
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
conversation history privacy70
conversation history privacy
70
Methodology
History privacy assessment
Evidence
Confidence: mediumLast verified: 2025-11-09
Trust & Transparency
78
documentation quality75
documentation quality
75
Methodology
Documentation completeness review
Evidence
Confidence: mediumLast verified: 2025-11-09
operation visibility80
operation visibility
80
Methodology
Logging and traceability assessment
Evidence
Confidence: highLast verified: 2025-11-09
open source transparency88
open source transparency
88
Methodology
Source code review
Evidence
Confidence: highLast verified: 2025-11-09
privacy risk disclosure70
privacy risk disclosure
70
Methodology
Privacy disclosure review
Evidence
Confidence: mediumLast verified: 2025-11-09
Operational Excellence
80
ease of setup75
ease of setup
75
Methodology
Setup complexity assessment
Evidence
Setup Documentation
Requires Google Cloud project setup and OAuth consent configuration
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
api performance82
api performance
82
Methodology
Performance benchmarking
Evidence
Confidence: mediumLast verified: 2025-11-09
reliability85
reliability
85
Methodology
Reliability analysis
Evidence
Confidence: highLast verified: 2025-11-09
operation coverage80
operation coverage
80
Methodology
Feature coverage assessment
Evidence
Confidence: highLast verified: 2025-11-09
community support75
community support
75
Methodology
Community support assessment
Evidence
Confidence: mediumLast verified: 2025-11-09
✨ Strengths
- •Comprehensive Gmail operations (read, send, search, label, attachments)
- •Built on reliable Gmail API with high uptime
- •Powerful email search with Gmail query language
- •OAuth 2.0 authentication with granular scope controls
- •Open source community implementation
- •Good for email automation and customer support workflows
⚠️ Limitations
- •Email content including body and attachments exposed to LLM provider
- •AI can send emails on user's behalf, risk of impersonation
- •Email addresses and contact information exposed
- •Can delete or trash emails if permissions granted
- •Subject to Gmail API rate limits (250 quota units/user/second)
- •Complex OAuth setup requiring Google Cloud project configuration
📊 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
api dependency: Gmail API, Google APIs Client Library
authentication: OAuth 2.0 with Google
first release: 2024-11
maintained by: Community
Use Case Ratings
code generation
70
Moderate applicability for email automation code generation
customer support
90
Excellent for email support automation and ticket processing
content creation
75
Useful for email newsletter creation and distribution
data analysis
78
Good for analyzing email patterns and communication metrics
research assistant
82
Useful for email research and contact organization
legal compliance
48
High risk of exposing privileged communications; not recommended
healthcare
42
High risk of HIPAA violations with patient communications
financial analysis
55
Risk of exposing financial communications and sensitive data
education
80
Good for educational email management and communication automation
creative writing
68
Moderate applicability for writer correspondence management