MCP Redis Diagnostics
Redis diagnostics MCP server — analyze memory usage, slowlog patterns, client connections, and keyspace health with AI-powered recommendations. Lightweight npx install, no Docker required.
MCP Redis Diagnostics
MCP server for Redis diagnostics — analyze memory usage, slowlog, client connections, and keyspace health with AI-powered recommendations.
Why This Tool?
Most Redis MCP servers are CRUD wrappers (get/set keys). RedisNexus offers diagnostics but targets enterprises (K8s, multi-tenant SaaS). This tool is the only lightweight npm package for deep Redis diagnostics — 7 tools covering memory fragmentation, slowlog patterns, client connection health, keyspace distribution, latency analysis, and configuration auditing. Install with npx, no Docker or SaaS required.
Pro Tier
Generate exportable diagnostic reports (HTML + PDF) with a Pro license key.
- Full JVM thread dump analysis report with actionable recommendations
- PDF export for sharing with your team
- Priority support
$9.00/month — Get Pro License
Pro license key activates the generate_report MCP tool in mcp-jvm-diagnostics.
Tools (7)
analyze_memory
Analyze Redis memory usage and fragmentation.
Detects:
- High memory fragmentation (>1.5x RSS/used ratio)
- Swap risk (fragmentation <1.0)
- Maxmemory pressure (approaching limit)
- Eviction patterns
- Missing maxmemory configuration
- Unsafe noeviction policy
analyze_slowlog
Analyze Redis SLOWLOG for slow commands.
Parameters:
count(number, default: 128) — Number of slowlog entries to retrieve
Detects:
- Dangerous O(N) commands: KEYS, SMEMBERS, HGETALL, SORT
- High latency commands (>10ms, >100ms thresholds)
- Command concentration patterns
- Full slowlog buffer (missing history)
analyze_clients
Analyze Redis client connections.
Detects:
- Blocked clients (BLPOP/BRPOP)
- Connection pool saturation (>80% maxclients)
- Idle connections (>5 minutes)
- Large output buffer memory
- Pub/sub subscriber patterns
analyze_keyspace
Analyze Redis keyspace distribution and cache effectiveness.
Detects:
- Low TTL coverage (<20% of keys)
- Low cache hit rate (<80%)
- Unbalanced database distribution
- High expiry/eviction rates
- Multiple database anti-pattern
analyze_latency
Analyze Redis latency events from the LATENCY subsystem.
Detects:
- Fork latency spikes (RDB/AOF background save blocking operations)
- AOF fsync delays and write latency
- Slow command processing (O(1) commands unexpectedly slow)
- Eviction and key expiry cycle delays
- Active defragmentation impact
- Increasing latency trends over time
Requires
latency-monitor-thresholdto be set in redis.conf (e.g.,CONFIG SET latency-monitor-threshold 100).
analyze_config
Analyze Redis configuration for security and reliability risks.
Detects:
- No maxmemory limit (unbounded memory growth, OOM risk)
- Unsafe eviction policy (noeviction causing errors at memory limit)
- Network exposure (bind 0.0.0.0 without protected-mode)
- Missing authentication (no requirepass)
- Disabled persistence (both AOF and RDB off — data loss on restart)
- Idle connection accumulation (timeout 0)
- Disabled TCP keepalive (dead connections undetected)
- Low server frequency (hz < 10 slowing background tasks)
analyze_performance
Comprehensive health assessment — runs all analyzers and produces a unified report.
Parameters:
slowlog_count(number, default: 128) — Number of slowlog entries
Installation
npm install -g mcp-redis-diagnostics
Or run directly:
npx mcp-redis-diagnostics
Configuration
Environment Variables
| Variable | Description | Default |
|---|---|---|
REDIS_URL | Redis connection string | redis://localhost:6379 |
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"redis-diagnostics": {
"command": "npx",
"args": ["-y", "mcp-redis-diagnostics"],
"env": {
"REDIS_URL": "redis://localhost:6379"
}
}
}
}
Redis with password:
{
"env": {
"REDIS_URL": "redis://:yourpassword@localhost:6379"
}
}
Quick Demo
Once configured, try these prompts in Claude:
- "Analyze my Redis memory usage — is there fragmentation?" — Shows used vs max memory, fragmentation ratio, eviction policy, and memory pressure issues
- "Check the Redis slowlog for dangerous commands" — Identifies O(N) commands like KEYS/SMEMBERS, high-latency patterns, and optimization suggestions
- "Run a complete Redis health check" — Unified report combining memory, slowlog, clients, keyspace, and latency analysis
"What's my cache hit rate? Are my TTLs configured properly?"
"Give me a full Redis health check"
Part of the MCP Java Backend Suite
This tool is part of a suite of MCP servers for backend developers:
- mcp-db-analyzer — PostgreSQL/MySQL/SQLite schema analysis
- mcp-jvm-diagnostics — Thread dump and GC log analysis
- mcp-migration-advisor — Flyway/Liquibase migration risk analysis
- mcp-spring-boot-actuator — Spring Boot health and metrics analysis
- mcp-redis-diagnostics — Redis memory, slowlog, and client diagnostics
Limitations & Known Issues
- Single Redis instance: Analyzes one Redis instance at a time. Does not support Redis Cluster topology discovery or Sentinel failover analysis.
- ACL restrictions: Some tools require specific Redis commands (SLOWLOG, CLIENT LIST, LATENCY). Redis ACLs may block these. The
analyze_performanceunified tool handles partial failures gracefully. - Latency monitoring: The
analyze_latencytool requireslatency-monitor-thresholdto be set in redis.conf. Without it, no latency events are captured. - Key-level analysis: Keyspace analysis uses
INFO keyspaceaggregates. Individual key inspection (e.g., finding the largest keys) requiresMEMORY USAGEper key, which is not performed to avoid impacting production. - Redis Cluster: No cluster-specific analysis (slot distribution, rebalancing, cross-node latency). Works against individual nodes only.
- Redis Modules: Module-specific commands and data types (RedisJSON, RediSearch, RedisTimeSeries) are not analyzed.
- Memory advisor: Memory recommendations are based on
INFO memorystats. For detailed memory breakdown by key type, useredis-cli --bigkeysexternally. - Fragmentation ratio: Memory fragmentation uses RSS vs. used memory ratio, which can be distorted by jemalloc. Values <1.0 may not always indicate swapping.
- Read-only: All commands are read-only (INFO, SLOWLOG GET, CLIENT LIST, LATENCY). No data or configuration is modified.
License
MIT
Related Servers
ODBC Server via PyODBC
An MCP server for connecting to databases like Virtuoso using ODBC drivers via pyodbc.
DART-MCP
Perform financial analysis using the DART API and Claude.
Unofficial Gene Ontology MCP Server
Access Gene Ontology (GO) data for ontology-based analysis, gene annotation research, and functional enrichment studies.
Macrostrat
Access geologic data from the Macrostrat API, including units, columns, minerals, and timescales.
Cloudera Iceberg MCP Server (via Impala)
Provides read-only access to Apache Iceberg tables using Apache Impala.
dbt-docs
MCP server for dbt-core (OSS) users as the official dbt MCP only supports dbt Cloud. Supports project metadata, model and column-level lineage and dbt documentation.
BigQuery
BigQuery database integration with schema inspection and query capabilities
Airtable
Access and manage Airtable bases, tables, and records using the Airtable Web API.
Keboola
Build robust data workflows, integrations, and analytics on a single intuitive platform.
Metabase MCP Server
Integrates AI assistants with the Metabase analytics platform.