Redis

Q: What can Redis do?

redis key-value store connection and session management, redis get/set/del command execution with type-aware responses, redis list operations (lpush, rpush, lpop, rpop, lrange) with queue semantics, redis hash operations (hset, hget, hgetall, hdel) with structured data support, redis set operations (sadd, smembers, sismember, sinter, sunion) with membership queries, redis key expiration and ttl management (expire, ttl, pexpire, persist), redis sorted set operations (zadd, zrange, zrank, zscore) with scoring and ranking, redis pattern-based key scanning (keys, scan) with glob pattern matching, redis database selection and namespace isolation (select, flushdb, dbsize)

MCP ServerFree

** - Interact with Redis key-value stores.

Open Source

/ 100

9 capabilities

Capabilities9 decomposed

redis key-value store connection and session management

Medium confidence

Establishes and maintains persistent connections to Redis instances through the Model Context Protocol transport layer, handling authentication via connection strings and managing socket lifecycle. The MCP server implements the standard server pattern with stdio or HTTP transport, routing client requests to Redis command handlers while maintaining connection pooling and error recovery for network interruptions.

Solves for

Connect an LLM agent to a Redis instance for persistent state managementEnable Claude or other MCP clients to authenticate and communicate with Redis without manual connection handlingMaintain session state across multiple tool invocations in an agentic workflow

Best for

AI agents requiring persistent key-value storage for session state

Teams building LLM-powered applications with Redis backends

Developers integrating Claude Desktop with existing Redis infrastructure

Requires

Redis server 4.0+ running and accessible on network

MCP client implementation (Claude Desktop, VS Code extension, or custom SDK)

Node.js 14+ or Python 3.8+ depending on server implementation language

Limitations

Archived and unmaintained — no security updates or bug fixes since archival

No built-in connection pooling optimization for high-concurrency scenarios

Single-instance support only — no cluster or sentinel failover handling

What makes it unique

Implements MCP server pattern for Redis, translating LLM tool calls into Redis commands through a standardized protocol transport rather than direct client libraries, enabling Claude and other MCP-compatible clients to interact with Redis without SDK dependencies

vs alternatives

Provides protocol-agnostic Redis access through MCP's standard interface, avoiding vendor lock-in to specific LLM SDKs while maintaining compatibility with any MCP-compliant client

redis get/set/del command execution with type-aware responses

Medium confidence

Executes fundamental Redis commands (GET, SET, DEL, EXISTS, INCR, APPEND, etc.) through MCP tool handlers, parsing command parameters from LLM tool calls and returning type-aware responses that preserve Redis data types (strings, integers, nil). The implementation maps LLM-friendly parameter schemas to Redis command syntax, handling type coercion and serialization for complex values.

Solves for

Store and retrieve simple key-value pairs from Redis via LLM tool callsIncrement counters or append to strings without manual Redis client codeDelete keys and check existence as part of agentic workflowsBuild LLM-driven state machines using Redis as the backing store

Best for

Solo developers building LLM agents with minimal infrastructure

Rapid prototyping of stateful AI applications

Teams migrating from in-memory state to persistent Redis storage

Requires

Redis server with basic string command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No transaction support (MULTI/EXEC) — each command executes independently

No Lua scripting — complex multi-step operations require multiple tool calls

Limited to basic string operations; no native support for Redis Streams or HyperLogLog

What makes it unique

Wraps Redis commands as MCP tools with JSON schema validation, allowing LLMs to call Redis operations through natural tool invocations rather than raw command syntax, with automatic response serialization that preserves type information

vs alternatives

Simpler integration path than direct Redis client libraries for LLM agents; MCP abstraction handles connection management and error handling transparently

redis list operations (lpush, rpush, lpop, rpop, lrange) with queue semantics

Medium confidence

Implements Redis list commands through MCP tools, enabling LLM agents to push/pop elements and retrieve ranges from lists. The server translates list operation parameters into Redis commands, handling list indexing, range queries, and blocking operations, with responses formatted as JSON arrays for LLM consumption.

Solves for

Implement task queues or job processing pipelines driven by LLM agentsMaintain ordered sequences of events or messages for agentic workflowsRetrieve historical data or conversation context from Redis listsBuild FIFO or LIFO data structures for agent state management

Best for

Agents managing task queues or work pipelines

Applications requiring ordered event logs or message histories

Teams building multi-step workflows with Redis as the coordination layer

Requires

Redis server with list command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No blocking operations (BLPOP, BRPOP) — agent must poll for new items

No list trimming or rotation — LTRIM requires separate tool call

Limited to sequential access; no random element access (LINDEX requires separate call)

What makes it unique

Exposes Redis list operations as MCP tools with queue-friendly semantics, automatically converting list responses to JSON arrays that LLMs can reason about, enabling agents to coordinate work through Redis-backed queues

vs alternatives

Provides queue abstraction without requiring dedicated message broker SDKs; leverages Redis' native list performance while maintaining MCP protocol compatibility

redis hash operations (hset, hget, hgetall, hdel) with structured data support

Medium confidence

Implements Redis hash commands through MCP tools, allowing LLM agents to store and retrieve structured data as field-value pairs within a single key. The server maps hash operations to JSON objects for LLM consumption, handling field-level access, bulk updates, and nested data serialization through JSON encoding.

Solves for

Store structured agent state (e.g., user profiles, session metadata) in RedisRetrieve and update specific fields of complex objects without full serializationImplement entity-attribute-value patterns for flexible data modelsBuild configuration stores or feature flags accessible to multiple agents

Best for

Applications with complex, semi-structured state requirements

Multi-agent systems sharing configuration or metadata

Teams building user profile or session management systems

Requires

Redis server with hash command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No nested hash support — only flat field-value pairs (nested data requires JSON serialization)

No atomic field updates with conditions — HSETNX requires separate call

No field expiration — entire hash expires together or not at all

What makes it unique

Translates Redis hashes to JSON objects in MCP tool responses, enabling LLMs to reason about structured data as native objects rather than flat key-value pairs, with automatic serialization/deserialization for nested data

vs alternatives

Provides structured data access without requiring schema definitions or ORM layers; Redis hashes offer better performance than serialized JSON strings for field-level updates

redis set operations (sadd, smembers, sismember, sinter, sunion) with membership queries

Medium confidence

Implements Redis set commands through MCP tools, enabling LLM agents to manage unordered collections of unique values and perform set algebra (intersection, union, difference). The server translates set operations to JSON arrays, handling membership tests, bulk additions, and set-to-set operations with automatic deduplication.

Solves for

Track unique items (e.g., user IDs, tags, permissions) without duplicatesCompute intersections of sets for recommendation or filtering workflowsImplement role-based access control using set membershipBuild tag systems or category management for LLM-driven applications

Best for

Applications requiring membership queries and set operations

Permission or role management systems

Recommendation engines using collaborative filtering patterns

Requires

Redis server with set command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No ordered sets — use Redis sorted sets (ZSET) for ranked data instead

Set operations (SINTER, SUNION) return results as unordered arrays

No atomic set-to-set moves (SMOVE) in single operation

What makes it unique

Exposes Redis set algebra operations as MCP tools, allowing LLMs to perform intersection/union/difference queries on collections without manual set logic, with automatic deduplication and membership validation

vs alternatives

Provides set semantics without requiring in-memory data structures; Redis sets offer O(1) membership tests and efficient set operations compared to array-based alternatives

redis key expiration and ttl management (expire, ttl, pexpire, persist)

Medium confidence

Implements Redis expiration commands through MCP tools, enabling LLM agents to set time-to-live (TTL) on keys, check remaining expiration time, and remove expiration. The server translates expiration parameters (seconds or milliseconds) into Redis commands, handling absolute and relative expiration times for cache invalidation and session timeout patterns.

Solves for

Implement session timeouts or temporary state that auto-cleans without manual deletionBuild cache layers with automatic expiration for LLM-driven applicationsManage rate-limiting buckets or temporary locks with automatic cleanupImplement sliding-window expiration for activity tracking

Best for

Applications requiring automatic data cleanup or session management

Cache layers with time-based invalidation

Rate-limiting or throttling implementations

Requires

Redis server with expiration support (any version 1.2+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No sub-second precision for expiration (millisecond precision available but not sub-millisecond)

No conditional expiration — cannot expire based on value or access patterns

Expiration is approximate — Redis may delay cleanup by up to 1 second

What makes it unique

Wraps Redis expiration commands as MCP tools with human-friendly TTL parameters, allowing LLMs to set and check key lifetimes without manual timestamp calculations, enabling automatic cleanup patterns in agentic workflows

vs alternatives

Provides automatic expiration without requiring separate cleanup jobs or cron tasks; Redis' native expiration is more efficient than application-level TTL tracking

redis sorted set operations (zadd, zrange, zrank, zscore) with scoring and ranking

Medium confidence

Implements Redis sorted set (ZSET) commands through MCP tools, enabling LLM agents to maintain ranked collections with numeric scores. The server translates sorted set operations to JSON arrays with score metadata, handling range queries by score or rank, and score updates, enabling leaderboards and priority queue patterns.

Solves for

Build leaderboards or ranking systems for LLM-driven games or competitionsImplement priority queues where agents process items by scoreTrack time-series data with timestamps as scores (e.g., event logs)Maintain sorted recommendations or search results with relevance scores

Best for

Applications requiring ranked or scored data

Leaderboard or competitive gaming systems

Priority queue implementations with dynamic scoring

Requires

Redis server with sorted set support (any version 1.2+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

Scores are floating-point; precision limited to IEEE 754 double precision

No multi-field sorting — only single numeric score per member

Range queries by score (ZRANGEBYSCORE) require separate tool call

What makes it unique

Exposes Redis sorted sets as MCP tools with score-aware responses, allowing LLMs to maintain ranked collections and perform range queries without manual sorting logic, with automatic score-to-member mapping

vs alternatives

Provides efficient ranking and range queries without requiring in-memory sorting; Redis sorted sets offer O(log N) insertion and O(log N + M) range queries compared to array-based alternatives

redis pattern-based key scanning (keys, scan) with glob pattern matching

Medium confidence

Implements Redis key discovery commands through MCP tools, enabling LLM agents to find keys matching glob patterns (KEYS) or iterate through keyspace with cursor-based scanning (SCAN). The server translates pattern parameters to Redis commands, returning matching key names as JSON arrays, with SCAN providing non-blocking iteration for large keyspaces.

Solves for

Discover keys matching a pattern (e.g., all session keys for a user)Iterate through Redis keyspace without blocking the serverImplement key cleanup or migration workflows based on naming patternsBuild key introspection tools for debugging or monitoring

Best for

Applications requiring key discovery or pattern-based operations

Debugging and monitoring tools for Redis instances

Data migration or cleanup workflows

Requires

Redis server with KEYS or SCAN support (SCAN added in Redis 2.8+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

KEYS command blocks Redis server — unsafe for production with large keyspaces (use SCAN instead)

SCAN cursor is opaque and server-specific — cannot be reused across server restarts

Pattern matching limited to glob syntax (*, ?, [abc]) — no regex support

What makes it unique

Wraps Redis SCAN as an MCP tool with cursor-based iteration, allowing LLMs to discover keys without blocking the server, with automatic pattern matching and result pagination for large keyspaces

vs alternatives

SCAN-based approach avoids server blocking unlike KEYS command; MCP abstraction handles cursor state management transparently across tool calls

redis database selection and namespace isolation (select, flushdb, dbsize)

Medium confidence

Implements Redis database selection and management commands through MCP tools, enabling LLM agents to switch between Redis logical databases (0-15 by default) and manage database-level operations. The server translates database commands to Redis, handling namespace isolation for multi-tenant or multi-environment scenarios, with DBSIZE providing database statistics.

Solves for

Isolate agent state across different environments (dev, staging, prod) using separate databasesImplement multi-tenant systems where each tenant has a dedicated Redis databaseClear test data or reset state by flushing entire databasesMonitor database size and key counts for capacity planning

Best for

Multi-tenant applications requiring logical isolation

Development workflows with separate test/staging/prod databases

Teams managing multiple Redis environments

Requires

Redis server with multiple databases enabled (default configuration)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

Database isolation is logical only — no encryption or access control between databases

FLUSHDB is destructive and non-recoverable — no undo or backup integration

Limited to 16 databases by default (configurable in Redis but not via MCP tool)

What makes it unique

Exposes Redis database selection as MCP tools, enabling agents to manage logical namespace isolation without manual connection switching, with automatic database context tracking across tool calls

vs alternatives

Provides logical isolation without requiring separate Redis instances; database-level separation is more efficient than key-prefix patterns for complete namespace isolation

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with Redis, ranked by overlap. Discovered automatically through the match graph.

MCP Server46

Redis MCP Server

Manage Redis keys, caches, and data structures via MCP.

list-based-ordered-data-sequenceskey-value-string-operations-with-expirationhash-based-structured-data-storageset-and-sorted-set-membership-operations

4 shared capabilities

MCP Server26

@upstash/mcp-server

MCP server for Upstash

redis data type command mapping and parameter validationupstash redis command execution via mcp protocol

2 shared capabilities

MCP Server29

@upstash/mcp-server

MCP server for Upstash

upstash kv (redis) key-value operations via mcp tools

1 shared capability

MCP Server48

trigger.dev

Trigger.dev – build and deploy fully‑managed AI agents and workflows

distributed locking and concurrency control

1 shared capability

Workflow39

Inngest

Event-driven durable workflow engine.

distributed queue with redis-backed state and lua-scripted atomicity

1 shared capability

Platform43

Upstash

Serverless data — Redis, Kafka, Vector DB, QStash with pay-per-request and edge support.

distributed redis cache with rest api and global replication

1 shared capability

Best For

✓AI agents requiring persistent key-value storage for session state
✓Teams building LLM-powered applications with Redis backends
✓Developers integrating Claude Desktop with existing Redis infrastructure
✓Solo developers building LLM agents with minimal infrastructure
✓Rapid prototyping of stateful AI applications
✓Teams migrating from in-memory state to persistent Redis storage
✓Agents managing task queues or work pipelines
✓Applications requiring ordered event logs or message histories

Known Limitations

⚠Archived and unmaintained — no security updates or bug fixes since archival
⚠No built-in connection pooling optimization for high-concurrency scenarios
⚠Single-instance support only — no cluster or sentinel failover handling
⚠Transport limited to stdio or HTTP; no native WebSocket support for long-lived connections
⚠No transaction support (MULTI/EXEC) — each command executes independently
⚠No Lua scripting — complex multi-step operations require multiple tool calls

Requirements

Redis server 4.0+ running and accessible on networkMCP client implementation (Claude Desktop, VS Code extension, or custom SDK)Node.js 14+ or Python 3.8+ depending on server implementation languageValid Redis connection string (redis://host:port or redis+unix:///path/to/socket)Redis server with basic string command support (any version 2.0+)MCP client with tool-calling capabilityNetwork connectivity to Redis instanceRedis server with list command support (any version 2.0+)

Input / Output

Accepts: connection string, Redis command parameters, key names and values, key name (string), value (string, integer, or JSON-serialized), expiration time in seconds (optional), command flags (NX, XX, EX, PX), list key name (string), element value (string or JSON-serialized), start and stop indices for LRANGE, count parameter for LPOP/RPOP (Redis 6.2+), hash key name (string), field name (string), field value (string or JSON-serialized object), multiple field-value pairs for HMSET/HSET, set key name (string), member value (string), multiple set keys for SINTER/SUNION/SDIFF, count parameter for SRANDMEMBER, TTL in seconds (integer) or milliseconds (integer), absolute Unix timestamp (for EXPIREAT/PEXPIREAT), sorted set key name (string), numeric score (float or integer), start and stop indices for ZRANGE, min and max scores for ZRANGEBYSCORE, glob pattern (string, e.g., 'user:*', 'session:*:data'), cursor for SCAN (string, starting with '0'), count hint for SCAN (integer, default 10), database index (integer 0-15), no parameters for DBSIZE or FLUSHDB

Produces: Redis command results (strings, lists, sets, hashes), status responses, error messages, string value, integer (for INCR, STRLEN, etc.), boolean (for EXISTS, SET with NX/XX), nil/null for missing keys, JSON array of list elements, integer (count of elements pushed/popped), single element (for LPOP/RPOP), nil for empty lists, JSON object representing hash (for HGETALL), string value (for HGET), integer (for HLEN, HEXISTS), array of field names or values (for HKEYS, HVALS), JSON array of set members (for SMEMBERS, SINTER, SUNION), boolean (for SISMEMBER), integer (for SCARD, SINTERCARD), random member (for SRANDMEMBER), integer (remaining TTL in seconds or milliseconds), boolean (success of EXPIRE/PERSIST operation), -1 for keys with no expiration, -2 for non-existent keys, JSON array of members with scores (for ZRANGE with WITHSCORES), integer (rank or count), float (score value), boolean (success of ZADD/ZREM), JSON array of matching key names (for KEYS), cursor and array of keys (for SCAN), empty array if no matches, integer (database index for SELECT, key count for DBSIZE), status message (for FLUSHDB), boolean (success of SELECT)

UnfragileRank

Adoption15%(30% weight)

Quality19%(25% weight)

Ecosystem30%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

9 capabilities

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** - Interact with Redis key-value stores.

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Capabilities9 decomposed

redis key-value store connection and session management

Medium confidence

Solves for

Best for

AI agents requiring persistent key-value storage for session state

Teams building LLM-powered applications with Redis backends

Developers integrating Claude Desktop with existing Redis infrastructure

Requires

Redis server 4.0+ running and accessible on network

MCP client implementation (Claude Desktop, VS Code extension, or custom SDK)

Node.js 14+ or Python 3.8+ depending on server implementation language

Limitations

Archived and unmaintained — no security updates or bug fixes since archival

No built-in connection pooling optimization for high-concurrency scenarios

Single-instance support only — no cluster or sentinel failover handling

What makes it unique

vs alternatives

Provides protocol-agnostic Redis access through MCP's standard interface, avoiding vendor lock-in to specific LLM SDKs while maintaining compatibility with any MCP-compliant client

redis get/set/del command execution with type-aware responses

Medium confidence

Solves for

Best for

Solo developers building LLM agents with minimal infrastructure

Rapid prototyping of stateful AI applications

Teams migrating from in-memory state to persistent Redis storage

Requires

Redis server with basic string command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No transaction support (MULTI/EXEC) — each command executes independently

No Lua scripting — complex multi-step operations require multiple tool calls

Limited to basic string operations; no native support for Redis Streams or HyperLogLog

What makes it unique

vs alternatives

Simpler integration path than direct Redis client libraries for LLM agents; MCP abstraction handles connection management and error handling transparently

redis list operations (lpush, rpush, lpop, rpop, lrange) with queue semantics

Medium confidence

Solves for

Best for

Agents managing task queues or work pipelines

Applications requiring ordered event logs or message histories

Teams building multi-step workflows with Redis as the coordination layer

Requires

Redis server with list command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No blocking operations (BLPOP, BRPOP) — agent must poll for new items

No list trimming or rotation — LTRIM requires separate tool call

Limited to sequential access; no random element access (LINDEX requires separate call)

What makes it unique

vs alternatives

Provides queue abstraction without requiring dedicated message broker SDKs; leverages Redis' native list performance while maintaining MCP protocol compatibility

redis hash operations (hset, hget, hgetall, hdel) with structured data support

Medium confidence

Solves for

Best for

Applications with complex, semi-structured state requirements

Multi-agent systems sharing configuration or metadata

Teams building user profile or session management systems

Requires

Redis server with hash command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No nested hash support — only flat field-value pairs (nested data requires JSON serialization)

No atomic field updates with conditions — HSETNX requires separate call

No field expiration — entire hash expires together or not at all

What makes it unique

vs alternatives

Provides structured data access without requiring schema definitions or ORM layers; Redis hashes offer better performance than serialized JSON strings for field-level updates

redis set operations (sadd, smembers, sismember, sinter, sunion) with membership queries

Medium confidence

Solves for

Best for

Applications requiring membership queries and set operations

Permission or role management systems

Recommendation engines using collaborative filtering patterns

Requires

Redis server with set command support (any version 2.0+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No ordered sets — use Redis sorted sets (ZSET) for ranked data instead

Set operations (SINTER, SUNION) return results as unordered arrays

No atomic set-to-set moves (SMOVE) in single operation

What makes it unique

vs alternatives

Provides set semantics without requiring in-memory data structures; Redis sets offer O(1) membership tests and efficient set operations compared to array-based alternatives

redis key expiration and ttl management (expire, ttl, pexpire, persist)

Medium confidence

Solves for

Best for

Applications requiring automatic data cleanup or session management

Cache layers with time-based invalidation

Rate-limiting or throttling implementations

Requires

Redis server with expiration support (any version 1.2+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

No sub-second precision for expiration (millisecond precision available but not sub-millisecond)

No conditional expiration — cannot expire based on value or access patterns

Expiration is approximate — Redis may delay cleanup by up to 1 second

What makes it unique

vs alternatives

Provides automatic expiration without requiring separate cleanup jobs or cron tasks; Redis' native expiration is more efficient than application-level TTL tracking

redis sorted set operations (zadd, zrange, zrank, zscore) with scoring and ranking

Medium confidence

Solves for

Best for

Applications requiring ranked or scored data

Leaderboard or competitive gaming systems

Priority queue implementations with dynamic scoring

Requires

Redis server with sorted set support (any version 1.2+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

Scores are floating-point; precision limited to IEEE 754 double precision

No multi-field sorting — only single numeric score per member

Range queries by score (ZRANGEBYSCORE) require separate tool call

What makes it unique

vs alternatives

Provides efficient ranking and range queries without requiring in-memory sorting; Redis sorted sets offer O(log N) insertion and O(log N + M) range queries compared to array-based alternatives

redis pattern-based key scanning (keys, scan) with glob pattern matching

Medium confidence

Solves for

Best for

Applications requiring key discovery or pattern-based operations

Debugging and monitoring tools for Redis instances

Data migration or cleanup workflows

Requires

Redis server with KEYS or SCAN support (SCAN added in Redis 2.8+)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

KEYS command blocks Redis server — unsafe for production with large keyspaces (use SCAN instead)

SCAN cursor is opaque and server-specific — cannot be reused across server restarts

Pattern matching limited to glob syntax (*, ?, [abc]) — no regex support

What makes it unique

Wraps Redis SCAN as an MCP tool with cursor-based iteration, allowing LLMs to discover keys without blocking the server, with automatic pattern matching and result pagination for large keyspaces

vs alternatives

SCAN-based approach avoids server blocking unlike KEYS command; MCP abstraction handles cursor state management transparently across tool calls

redis database selection and namespace isolation (select, flushdb, dbsize)

Medium confidence

Solves for

Best for

Multi-tenant applications requiring logical isolation

Development workflows with separate test/staging/prod databases

Teams managing multiple Redis environments

Requires

Redis server with multiple databases enabled (default configuration)

MCP client with tool-calling capability

Network connectivity to Redis instance

Limitations

Database isolation is logical only — no encryption or access control between databases

FLUSHDB is destructive and non-recoverable — no undo or backup integration

Limited to 16 databases by default (configurable in Redis but not via MCP tool)

What makes it unique

Exposes Redis database selection as MCP tools, enabling agents to manage logical namespace isolation without manual connection switching, with automatic database context tracking across tool calls

vs alternatives

Provides logical isolation without requiring separate Redis instances; database-level separation is more efficient than key-prefix patterns for complete namespace isolation

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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Redis

Capabilities9 decomposed

redis key-value store connection and session management

redis get/set/del command execution with type-aware responses

redis list operations (lpush, rpush, lpop, rpop, lrange) with queue semantics

redis hash operations (hset, hget, hgetall, hdel) with structured data support

redis set operations (sadd, smembers, sismember, sinter, sunion) with membership queries

redis key expiration and ttl management (expire, ttl, pexpire, persist)

redis sorted set operations (zadd, zrange, zrank, zscore) with scoring and ranking

redis pattern-based key scanning (keys, scan) with glob pattern matching

redis database selection and namespace isolation (select, flushdb, dbsize)

Related Artifactssharing capabilities

Redis MCP Server

@upstash/mcp-server

@upstash/mcp-server

trigger.dev

Inngest

Upstash

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Redis

Are you the builder of Redis?

Get the weekly brief

Data Sources

Redis

Capabilities9 decomposed

redis key-value store connection and session management

redis get/set/del command execution with type-aware responses

redis list operations (lpush, rpush, lpop, rpop, lrange) with queue semantics

redis hash operations (hset, hget, hgetall, hdel) with structured data support

redis set operations (sadd, smembers, sismember, sinter, sunion) with membership queries

redis key expiration and ttl management (expire, ttl, pexpire, persist)

redis sorted set operations (zadd, zrange, zrank, zscore) with scoring and ranking

redis pattern-based key scanning (keys, scan) with glob pattern matching

redis database selection and namespace isolation (select, flushdb, dbsize)

Related Artifactssharing capabilities

Redis MCP Server

@upstash/mcp-server

@upstash/mcp-server

trigger.dev

Inngest

Upstash

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Redis

Are you the builder of Redis?

Get the weekly brief

Data Sources