tanstack-ai-memory-redis

tanstack-ai-memory-redis is a skill for Claude Code from TanStack/ai. It costs 52 tokens per session (862 once invoked), scanned A, original, MIT.

A Redis-backed memory adapter for TanStack AI. Redis is a fast data store; this adapter saves conversation memories there and ranks possible matches using text, optional similarity, freshness, and importance.

In plain words
What is it for?
Use it to connect TanStack AI memory to an existing ioredis or node-redis client, then save and recall conversation information through `memoryMiddleware`.
Why use it?
It provides production memory storage without requiring a vector index, while still narrowing and ranking the memories returned to the assistant.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the tanstack-ai plugin — 47 skills shipped together

Good fit Use it to connect TanStack AI memory to an existing ioredis or node-redis client, then save and recall conversation information through memoryMiddleware.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tanstack/ai/tanstack-ai-memory-redis
About the project

TanStack AI is a TypeScript SDK for building applications that stream AI responses, call tools, run agents, produce structured output, and handle multimodal or realtime interactions. Developers use it across frameworks and AI providers through shared typed interfaces and provider adapters. The catalogue entries are add-ons for working with this SDK.

TanStack/ai · 3,199 stars · on GitHub · tanstack.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TanStack/ai --skill tanstack-ai-memory-redis
Clone the repo
git clone --depth 1 https://github.com/TanStack/ai

Made for: Claude Code.

Or install tanstack-ai, the plugin that ships this one along with the rest of its 47 skills.

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README.md
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Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 862 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.00862
Opus 5.5 $0.00021 $0.00345
Sonnet 5.5 $0.00010 $0.00172
Haiku 4.5 $0.00005 $0.00086

Measured 1mo ago against content hash 1fdbbd83daa0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tanstack-ai-memory-redis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/ai-memory/skills/tanstack-ai-memory-redis/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Redis Memory Adapter

Production-grade recall/save adapter backed by plain Redis (no vector index required). Ranks client-side (lexical + optional cosine + recency + importance).

Setup

Bring your own Redis client. ioredis wires in directly; redis (node-redis v4+) needs a small wrapper.

Option A: ioredis

import Redis from 'ioredis'
import { memoryMiddleware } from '@tanstack/ai-memory'
import { redis } from '@tanstack/ai-memory/redis'

const client = new Redis(process.env.REDIS_URL ?? 'redis://localhost:6379')
const memory = redis({ redis: client, prefix: 'myapp:memory' })

// Resolve scope per request from the server-validated session — never from req.body.
function memoryFor(session: { userId: string; threadId: string }) {
  return memoryMiddleware({
    adapter: memory,
    scope: { threadId: session.threadId, userId: session.userId },
  })
}

Option B: redis (node-redis v4+)

import { createClient } from 'redis'
import { memoryMiddleware } from '@tanstack/ai-memory'
import { redis, fromNodeRedis } from '@tanstack/ai-memory/redis'

const client = createClient({ url: process.env.REDIS_URL })
await client.connect()

const memory = redis({
  redis: fromNodeRedis(client),
  prefix: 'myapp:memory',
})

function memoryFor(session: { userId: string; threadId: string }) {
  return memoryMiddleware({
    adapter: memory,
    scope: { threadId: session.threadId, userId: session.userId },
  })
}

node-redis exposes a camelCase API (sAdd, mGet); fromNodeRedis translates it to the lowercase RedisLike shape. Passing a raw node-redis client without the wrapper throws client.sadd is not a function.

redis() accepts the same topK / minScore / kinds / embedder / extract options as inMemory().

Storage model

{prefix}:record:{id}                                          -> JSON record
{prefix}:index:{tenantId or _}:{userId or _}:{threadId}       -> Set<id>

save writes the record and adds it to the scope's index set; recall loads the set, scores, and renders. Scope values are escaped (:, \, and _) so a delimiter or the unset placeholder inside a dim can't collide two scopes.

Read the full file on GitHub · 95 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · +11 lines 1fdbbd83daa0
  2. 1mo ago First seen · 84 lines · 52 tokens per session scan A e919d86b5987

Subscribe to this mod's changes

tanstack-ai-memory-redis is a skill published in the GitHub repository TanStack/ai (3,199 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 862 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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