Upstash Redis JS
UpstashOfficialCreated by Upstash
- Skill
- Tool integration
- Software development
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a complete reference for the @upstash/redis SDK, an HTTP-based Redis client designed for serverless environments like Vercel, Cloudflare Workers, and edge runtimes. It covers core data structures, advanced features like pipelines and Lua scripting, common architectural patterns such as caching and session management, and migration paths from traditional Redis clients. The SDK features automatic serialization of JavaScript types, simplifying data handling for developers.
What it does
- Provides methods for interacting with Redis data structures including strings, hashes, lists, sets, sorted sets, and JSON.
- Supports advanced Redis features like pipelines, MULTI/EXEC transactions, and Lua scripting.
- Includes patterns for implementing caching, rate limiting, distributed locks, and session management.
- Enables vector search and full-text search capabilities within Redis.
- Handles automatic serialization and deserialization of native JavaScript types.
- Offers migration guidance for developers moving from ioredis or node-redis.
When to use it
- When building serverless applications that require a Redis-compatible key-value store.
- When implementing caching, session storage, or leaderboards in edge runtimes.
- When you need to perform atomic operations or complex server-side logic via Lua scripts.
- When migrating existing Node.js applications to a serverless architecture.
- When integrating AI agent memory or RAG tools using Redis.
Advantages
- Serverless-friendly HTTP-based architecture eliminates connection pooling issues.
- Automatic serialization removes the need for manual JSON parsing.
- Comprehensive support for modern Redis features including JSON and vector search.
- Well-defined patterns for common use cases like rate limiting and distributed locks.
- Seamless integration with popular frameworks like Next.js and Vercel.
Usage examples
- “How do I store a user object in Redis using the Upstash SDK?”
- The agent will demonstrate using redis.set('user:1', { name: 'Alice' }), highlighting that the SDK automatically handles JSON serialization.
- “Show me how to implement a simple counter in Redis.”
- The agent will provide code using redis.incr('counter') and explain that the SDK returns the incremented number directly without manual parsing.
- “How can I perform multiple operations atomically?”
- The agent will explain the use of redis.multi() or pipelines to batch commands and ensure atomic execution.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/upstash/upstash-redis-js/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip upstash-redis-js.zip -d .agents/skills
Documentation by Upstash
Upstash Redis SDK - Complete Skills Guide
This directory contains comprehensive guides for using the @upstash/redis SDK. These skill files are designed to help developers and AI assistants understand and use the SDK effectively.
Bundled docs and source
Before writing or debugging SDK code, check node_modules/@upstash/redis/docs/ for bundled docs and node_modules/@upstash/redis/src/ for readable TypeScript source. Read and search the relevant files when present; otherwise use the references in this skill.
Installation
npm install @upstash/redisQuick Start
Basic Initialization
import { Redis } from "@upstash/redis";
// Initialize with explicit credentials
const redis = new Redis({
url: "UPSTASH_REDIS_REST_URL",
token: "UPSTASH_REDIS_REST_TOKEN",
});
// Or initialize from environment variables
const redis = Redis.fromEnv();Environment Variables
Set these in your .env file:
UPSTASH_REDIS_REST_URL=https://your-redis.upstash.io
UPSTASH_REDIS_REST_TOKEN=your-token-hereNo credentials yet? If you're an agent that needs scratch Redis and the user hasn't provided a database, you can mint a temporary one with a single POST to
https://upstash.com/start-redis(3-day TTL, no signup).
Skill Files Overview
Data Structures (data-structures/)
Redis data types with auto-serialization examples:
strings.md - GET, SET, INCR, DECR, APPEND with automatic type handling
hashes.md - HSET, HGET, HMGET with object serialization
lists.md - LPUSH, RPUSH, LRANGE with array handling
sets.md - SADD, SMEMBERS, set operations
sorted-sets.md - ZADD, ZRANGE, ZRANK, leaderboard patterns
json.md - JSON.SET, JSON.GET, JSONPath queries for nested objects
streams.md - XADD, XREAD, XGROUP, consumer groups
arrays.md - ARSET, ARINSERT, ARSCAN, ARGREP, AROP, ring buffers with ARRING on sparse index-addressed arrays
vector-indexes.md - VECTOR.CREATE, VECTOR.ADD, VECTOR.QUERY nearest-neighbour search inside Redis via redis.vector
Advanced Features (advanced-features/)
Complex operations and optimizations:
auto-pipeline.md - Automatic request batching, performance optimization
pipeline-and-transactions.md - Manual pipelines, MULTI/EXEC for atomic operations
scripting.md - Lua scripts, EVAL, EVALSHA for server-side logic
Patterns (patterns/)
Common use cases and architectural patterns:
caching.md - Cache-aside, write-through, TTL strategies
rate-limiting.md - Integration with @upstash/ratelimit package
session-management.md - Session storage and user state management
distributed-locks.md - Lock implementations, deadlock prevention
leaderboard.md - Sorted set leaderboards, real-time rankings
Performance (performance/)
Optimization techniques and best practices:
batching-operations.md - MGET, MSET, batch operations
pipeline-optimization.md - When to use pipelines, performance tips
ttl-expiration.md - Key expiration strategies, memory management
data-serialization.md - Deep dive into auto serialization, custom serializers, edge cases
error-handling.md - Error types, retry strategies, timeout handling, debugging tips
redis-replicas.md - Global database setup, read replicas, read-your-writes consistency
Search (search/)
Full-text search, filtering, and aggregation extension for Redis:
overview.md - Schema definition, field types, pitfalls, package overview
commands/querying.md - Query and count with filters, pagination, sorting, highlighting
commands/aggregating.md - Metric aggregations ($avg, $sum, $stats), bucket aggregations ($terms, $range, $histogram, $facet)
commands/index-management.md - Create, describe, drop indexes (including stream indexes over XADD entries), waitIndexing
commands/aliases.md - Index aliases for zero-downtime reindexing
adapters.md - Using search with node-redis and ioredis via @upstash/search-redis and @upstash/search-ioredis
Migrations (migrations/)
Migration guides from other libraries:
from-ioredis.md - Migration from ioredis, key differences, serialization changes
from-redis-node.md - Migration from node-redis, API differences
Common Mistakes (Especially for LLMs)
❌ Mistake 1: Treating Everything as Strings
// ❌ WRONG - Don't do this with @upstash/redis
await redis.set("count", "42"); // Stored as string "42"
const count = await redis.get("count");
const incremented = parseInt(count) + 1; // Manual parsing needed
// ✅ CORRECT - Let the SDK handle it
await redis.set("count", 42); // Stored as number
const count = await redis.get("count");
const incremented = count + 1; // Just use it❌ Mistake 2: Manual JSON Serialization
// ❌ WRONG - Unnecessary with @upstash/redis
await redis.set("user", JSON.stringify({ name: "Alice" }));
const user = JSON.parse(await redis.get("user"));
// ✅ CORRECT - Automatic handling
await redis.set("user", { name: "Alice" });
const user = await redis.get("user");Quick Command Reference
// Strings
await redis.set("key", "value");
await redis.get("key");
await redis.incr("counter");
await redis.decr("counter");
// Hashes
await redis.hset("user:1", { name: "Alice", age: 30 });
await redis.hget("user:1", "name");
await redis.hgetall("user:1");
// Lists
await redis.lpush("tasks", "task1", "task2");
await redis.rpush("tasks", "task3");
await redis.lrange("tasks", 0, -1);
// Sets
await redis.sadd("tags", "javascript", "redis");
await redis.smembers("tags");
// Sorted Sets
await redis.zadd("leaderboard", { score: 100, member: "player1" });
await redis.zrange("leaderboard", 0, -1);
// JSON
await redis.json.set("user:1", "$", { name: "Alice", address: { city: "NYC" } });
await redis.json.get("user:1");
// Expiration
await redis.setex("session", 3600, { userId: "123" });
await redis.expire("key", 60);
await redis.ttl("key");Best Practices
Use environment variables for credentials, never hardcode
Leverage auto-serialization - pass native JavaScript types
Use TypeScript types for better type safety
Set appropriate TTLs to manage memory
Use pipelines for multiple operations
Namespace your keys (e.g.,
user:123,session:abc)
AI agents: use AgentKit
For agent state on Redis — memory, chat history, RAG search tools, tool caching, rate limiting, chat persistence, resumable streams, locks — use Upstash AgentKit instead of hand-rolling it on @upstash/redis. Pick the adapter for the framework and follow its docs page:
| Framework | Package | Docs |
|---|---|---|
| Vercel AI SDK | @upstash/agentkit-ai-sdk | https://upstash.com/docs/redis/sdks/agentkit/ai-sdk |
| TanStack AI | @upstash/agentkit-tanstack-ai | https://upstash.com/docs/redis/sdks/agentkit/tanstack-ai |
| Vercel Eve | @upstash/agentkit-eve, @upstash/agentkit-eve-extension | https://upstash.com/docs/redis/sdks/agentkit/eve |
Resources
Getting Help
For detailed information on specific topics, refer to the individual skill files in the skills/ directory. Each file contains comprehensive examples, use cases, and best practices for its topic.
Files
- ATTRIBUTION.mdAdded by AutoGineer883 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md9.1 KiB
- advanced-features/auto-pipeline.md1.3 KiB
- advanced-features/pipeline-and-transactions.md2.5 KiB
- advanced-features/scripting.md2.8 KiB
- data-structures/arrays.md3.7 KiB
- data-structures/hashes.md1.8 KiB
- data-structures/json.md3.6 KiB
- data-structures/lists.md2.1 KiB
- data-structures/sets.md2.8 KiB
- data-structures/sorted-sets.md3.9 KiB
- data-structures/streams.md5.0 KiB
- data-structures/strings.md2.1 KiB
- data-structures/vector-indexes.md2.5 KiB
- migrations/from-ioredis.md3.6 KiB
- migrations/from-redis-node.md4.2 KiB
- patterns/caching.md1.3 KiB
- patterns/distributed-locks.md3.6 KiB
- patterns/leaderboard.md4.1 KiB
- patterns/rate-limiting.md4.7 KiB
- patterns/session-management.md5.0 KiB
- performance/batching-operations.md2.0 KiB
- performance/data-serialization.md3.4 KiB
- performance/error-handling.md3.8 KiB
- performance/pipeline-optimization.md2.4 KiB
- performance/redis-replicas.md484 B
- performance/ttl-expiration.md775 B
- search/adapters.md2.8 KiB
- search/commands/aggregating.md5.8 KiB
- search/commands/aliases.md2.1 KiB
- search/commands/index-management.md4.6 KiB
- search/commands/querying.md6.6 KiB
- search/overview.md6.5 KiB
data-structures/vector-indexes.md
Vector Indexes
Overview
A vector index stores embeddings under string IDs inside Redis and answers approximate nearest-neighbour queries. It lives at an ordinary Redis key (EXISTS, EXPIRE, DEL work on it). This is the VECTOR.* command family of Upstash Redis, which is separate from the standalone Upstash Vector database and its @upstash/vector SDK (see the upstash-vector-js skill).
Good For
Semantic search or RAG next to data already in Redis, without another service
Semantic caching of LLM responses
Small to medium embedding sets that share a Redis database's lifecycle
Prefer Upstash Vector (@upstash/vector) for metadata filtering, namespaces, hybrid/sparse search, or built-in embedding models.
Examples
import { Redis } from "@upstash/redis";
const redis = Redis.fromEnv();
// dimension (1-32768) and metric are fixed for the life of the index
const index = await redis.vector.createIndex({
name: "docs",
dimension: 1536,
metric: "COSINE", // COSINE | EUCLIDEAN | DOT
existsOk: true, // idempotent start-up path
});
// Handle to an existing index, no round trip
const same = redis.vector.index("docs");
// Upsert: 1 = added, 0 = replaced
await index.add("doc-1", embedding); // number[]
await index.add("doc-2", new Float32Array(embedding)); // sent as base64 FP32
await index.add("doc-3", { base64: openAiBase64Embedding }); // encoding_format: "base64"
// Nearest neighbours, best first. Scores are normalized to 0..1 for every metric.
const hits = await index.query({ vector: queryEmbedding, topK: 5, profile: "PRECISE" });
// [{ id: "doc-1", score: 0.93 }, ...]
await index.get("doc-1"); // number[] (float32 precision) | null
await index.count(); // 3
await index.info(); // { dimension: 1536, metric: "COSINE" } | null if missing
await index.delete("doc-1"); // 1 | 0
await index.drop(); // 1 | 0Common Mistakes
Importing
@upstash/vectorfor these commands. They are part of@upstash/redisand use the Redis REST URL and token.Changing
dimensionormetricon an existing index. Drop and recreate it instead.Comparing
get()output to the original embedding exactly. Values are stored as 32-bit floats.Expecting
redis.pipeline()orredis.multi()to batch vector commands. Like search, the vector namespace is not available on pipelines: every call is its own request, so bulk loads should be chunked and run withPromise.allinstead.Checking existence with
count(). It returns0for both a missing and an empty index;info()returnsnullonly when the index is missing.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Node.js
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Upstash
- Publisher
- Upstash (Official)
- Source
- upstash/skills · skills/upstash-redis-js · commit 9f9e3e5
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Upstash or Upstash.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download upstash-redis-js.zip