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MCP Redis Server

Anthropic (Archived)

78·Strong

Overall Trust Score

Community-maintained MCP server for Redis cache and data structure operations. Enables AI models to interact with Redis for key-value operations, pub/sub messaging, lists, sets, sorted sets, and hashes. Essential for AI-powered caching strategies, session management, and real-time data workflows.

cache
database
mcp
model-context-protocol
Version: 2025.4.24
Last Evaluated: November 9, 2025
Official Website →

Trust Vector

Performance & Reliability

88
operation speed
95
Methodology
Performance benchmarking
Evidence
Redis Performance
Extremely fast in-memory operations (sub-millisecond latency)
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command reliability
90
Methodology
Command execution testing
Evidence
Redis Client
Built on official Redis clients with high reliability
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
data structure accuracy
92
Methodology
Data structure testing
Evidence
Redis Data Types
Accurate handling of strings, lists, sets, sorted sets, and hashes
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
connection stability
85
Methodology
Connection stability testing
Evidence
Redis Connection Handling
Stable connections with automatic reconnection
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
pubsub reliability
82
Methodology
Pub/sub testing
Evidence
Redis Pub/Sub
Reliable pub/sub messaging with guaranteed delivery to subscribers
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Security

70
authentication security
75
Methodology
Authentication mechanism review
Evidence
Redis Security
Supports password authentication and ACLs (Redis 6+)
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
connection string exposure
62
Methodology
Credential security analysis
Evidence
MCP Security Model
Redis connection string with password stored locally; accessible to AI
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command injection risk
68
Methodology
Command injection testing
Evidence
Security Analysis
AI can execute arbitrary Redis commands within ACL permissions
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
data deletion risk
65
Methodology
Destructive operation testing
Evidence
Redis Commands
AI can delete keys, flush databases if permissions allow
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
acl enforcement
78
Methodology
ACL enforcement testing
Evidence
Redis ACL
Redis 6+ ACLs provide granular command and key restrictions
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
audit logging
72
Methodology
Audit logging review
Evidence
Redis Monitoring
Limited built-in audit logging; requires external monitoring
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Privacy & Compliance

68
cached data exposure
65
Methodology
Data flow analysis
Evidence
MCP Data Flow
Cached data including session tokens and user data sent to LLM provider
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
session data privacy
60
Methodology
Session privacy assessment
Evidence
Privacy Analysis
Session data and user tokens commonly stored in Redis may be exposed
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
key pattern exposure
72
Methodology
Key privacy assessment
Evidence
Privacy Analysis
Key naming patterns may reveal application structure and data relationships
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
third party data sharing
68
Methodology
Data sharing analysis
Evidence
LLM Provider Policies
Cache content shared with LLM provider per their privacy policy
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
ttl data persistence
70
Methodology
Data persistence assessment
Evidence
Redis TTL
Temporary data may be captured before expiration
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Trust & Transparency

77
documentation quality
73
Methodology
Documentation completeness review
Evidence
Redis MCP Docs
Basic documentation but community-maintained with evolving coverage
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09
command visibility
80
Methodology
Command logging assessment
Evidence
MCP Protocol
All Redis commands logged in MCP transaction logs
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
open source transparency
88
Methodology
Source code review
Evidence
GitHub Repository
Open source community implementation
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command coverage clarity
68
Methodology
API documentation review
Evidence
MCP Server Documentation
Limited documentation of supported Redis commands
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

Operational Excellence

85
ease of setup
88
Methodology
Setup complexity assessment
Evidence
Setup Documentation
Simple setup requiring Redis connection URL
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command performance
95
Methodology
Performance benchmarking
Evidence
Redis Performance
Extremely fast operations (sub-millisecond for most commands)
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
reliability
85
Methodology
Reliability analysis
Evidence
Redis Stability
Built on mature Redis clients with high reliability
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
command coverage
78
Methodology
Feature coverage assessment
Evidence
Redis MCP Server
Covers key-value ops, lists, sets, sorted sets, hashes, and pub/sub
Date: 2025-11-16
Confidence: highLast verified: 2025-11-09
community support
75
Methodology
Community support assessment
Evidence
GitHub Community
Community-maintained with moderate activity
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-09

✨ Strengths

  • •Extremely fast sub-millisecond operations for all data types
  • •Comprehensive Redis data structure support (strings, lists, sets, hashes)
  • •Built on official Redis clients with high reliability
  • •Excellent for real-time caching and session management automation
  • •Open source community implementation
  • •Supports pub/sub for real-time messaging patterns

⚠️ Limitations

  • •Cached data including session tokens exposed to LLM provider
  • •AI can delete keys and flush databases within permission scope
  • •Redis connection strings with passwords accessible to AI
  • •Session data and user tokens commonly stored in Redis may be exposed
  • •Limited built-in audit logging capabilities
  • •Key naming patterns may reveal application architecture

📊 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: Redis client libraries (ioredis, redis-py)
authentication: Redis password, ACLs (Redis 6+)
first release: 2024-11
maintained by: Community

Use Case Ratings

code generation

82

Good for generating caching logic and Redis integration code

customer support

70

Useful for analyzing session data and user activity patterns

content creation

60

Limited applicability; mainly for cached content management

data analysis

85

Excellent for analyzing real-time data and cache performance metrics

research assistant

72

Useful for researching caching strategies and data patterns

legal compliance

52

High risk of exposing cached sensitive data; requires strict controls

healthcare

48

High risk of exposing patient session data; not recommended

financial analysis

58

Moderate risk; cached financial data exposure concerns

education

88

Excellent for teaching caching, in-memory databases, and real-time systems

creative writing

55

Limited applicability for writing workflows