Skalex

AI-first · Isomorphic · Zero-dependency · Local-first

Skalex ships vector search, agent memory, natural language queries, an MCP server, and AES-256-GCM encryption in a single zero-dependency package - no server, no config, no external services. One npm install skalex on Node.js, Bun, Deno, browsers, and edge runtimes. All AI capabilities - cosine similarity search, semantic agent memory with compression, db.ask() NLP queries via any LLM, and a one-line MCP server for Claude Desktop and Cursor - are built into the core with zero additional dependencies.

Architecture + fit: all data lives in your process's heap - db.connect() loads the full dataset for instant, zero-overhead access. Storage adapters control where data persists, not how much fits. Designed for single-process, local-first workloads where the dataset fits in RAM: AI agents, CLI tools, desktop apps, edge workers, offline-first apps. Not a replacement for PostgreSQL or MongoDB for large-scale, multi-process, or distributed systems.

Features

Zero overhead. Maximum reach.

• Zero dependencies: install the package, nothing else. No driver, no ORM, no server process.
• Full build matrix: ESM, ESM minified, CJS, CJS minified, browser ESM (dist/skalex.browser.js, no node:* imports), UMD/IIFE (dist/skalex.umd.min.js, CDN default)
• Runs everywhere: Node.js ≥18, Bun, Deno 2.x, browser (Chrome/Firefox/Safari), edge runtimes; verified by a 787-test cross-runtime suite
• Pluggable storage: FsAdapter (Node), LocalStorageAdapter (browser), EncryptedAdapter (AES-256-GCM), or bring your own

Queries that scale with your data.

• Full operator set: $eq $ne $gt $gte $lt $lte $in $nin $regex $fn
• Dot-notation nested field queries
• Secondary field indexes: O(1) lookups via IndexEngine
• Unique constraints, filter pre-sorter for performance

Your data stays clean.

• Zero-dependency schema validation: type, required, unique, enum
• Strict mode: createCollection(name, { strict: true }) rejects unknown fields; onSchemaError: "warn" | "strip" for softer handling
• Versioned migrations: addMigration({ version, up }), auto-run on connect()
• TTL documents: insertOne(doc, { ttl: "30m" }), swept on connect; defaultTtl per collection; ttlSweepInterval for live processes
• Transactions: in-memory snapshot/rollback; writes suppressed from disk during fn(); concurrent transactions serialised; external side effects and direct collection mutations are not rolled back
• Change log: createCollection(name, { changelog: true }), point-in-time restore
• Soft deletes: createCollection(name, { softDelete: true }), col.restore(), { includeDeleted }
• Document versioning: createCollection(name, { versioning: true }), auto-increments _version
• Capped collections: createCollection(name, { maxDocs: N }), FIFO eviction

Semantic search, built in.

• insertOne / insertMany with { embed: "field" }: auto-embed on insert
• collection.search(query, { filter, limit, minScore }): cosine similarity + hybrid
• collection.similar(id): nearest-neighbour lookup
• db.embed(text): direct embedding access
• Built-in adapters: OpenAI (text-embedding-3-small) and Ollama (local, zero cost)

Your database speaks English.

• db.ask(collection, nlQuery): translate natural language to a filter via LLM; results cached
• db.useMemory(sessionId): episodic agent memory with remember, recall, context, compress
• Built-in language model adapters: OpenAI, Anthropic, Ollama
• db.schema(collection): infer or return declared schema as a plain object

Know exactly what's happening.

• collection.count / sum / avg / groupBy: aggregation with optional filter and dot-notation
• db.stats(collection?): count, estimated size, average doc size
• slowQueryLog option + db.slowQueries(): capture slow find and search calls

React to every change.

• collection.watch(filter?, callback?): observe mutations; callback or AsyncIterableIterator
• db.watch(callback): cross-collection global observer; fires for every mutation across all collections
• Events: { op, collection, doc, prev? } emitted after every insert, update, delete, restore

AI agents, natively wired.

• db.mcp(opts): expose the database as MCP tools for AI agents
• Compatible with Claude Desktop, Cursor, and any MCP client
• stdio transport (default) and http + SSE transport
• Tools: find, insert, update, delete, search, ask, schema, collections
• Access control: scopes map per collection; read / write / admin

Extend anything.

• db.use(plugin): register pre/post hooks on all operations
• Hooks: beforeInsert, afterInsert, beforeUpdate, afterUpdate, beforeDelete, afterDelete, beforeFind, afterFind, beforeSearch, afterSearch
• All hooks awaited in order; errors propagate to the caller

Full visibility per session.

• db.sessionStats(sessionId?): reads, writes, lastActive per session
• session option on all reads and writes: automatic accumulation

Deploy anywhere.

• D1Adapter: Cloudflare D1 / Workers edge SQLite
• BunSQLiteAdapter: Bun-native bun:sqlite; :memory: or file path
• LibSQLAdapter: LibSQL / Turso client adapter

Built for developers who value their time.

• db.transaction(fn): in-memory snapshot/rollback; writes serialised and suppressed from disk until fn() resolves
• db.seed(fixtures): idempotent fixture seeding
• db.dump() / db.inspect(): snapshot and metadata
• db.namespace(id): isolated sub-instances per tenant / user
• db.import(path): JSON import; collection name derived from filename
• db.renameCollection(from, to): in-memory + on-disk rename
• collection.upsert(), collection.upsertMany(docs, matchKey), insertOne({ ifNotExists }): safe idempotent writes
• autoSave: true: persist after every write without { save: true } on every call
• encrypt: { key }: AES-256-GCM at-rest encryption, transparent to all callers
• session option on all reads and writes: audit trail + session stats
• debug: true: connect/disconnect logging

Installation

npm install skalex@alpha

v4.0.0-alpha.1 is the current release. npm install skalex installs the last stable v3 - use @alpha to get v4.

Requires Node.js ≥ 18.

Or via CDN (no bundler, no npm - browser direct):

ESM - recommended for real browser apps; connectors import alongside Skalex:

<script type="module">
  import Skalex from "https://cdn.jsdelivr.net/npm/skalex@4.0.0-alpha.1/dist/skalex.browser.js";
  import { LocalStorageAdapter } from "https://cdn.jsdelivr.net/npm/skalex@4.0.0-alpha.1/src/connectors/storage/browser.js";
  // browser.js also exports EncryptedAdapter for AES-256-GCM at-rest encryption

  const db = new Skalex({ adapter: new LocalStorageAdapter({ namespace: "myapp" }) });
  await db.connect();
</script>

With npm + bundler, use the connectors subpackage:

import Skalex from 'skalex';
// Scoped barrels (tree-shakeable, recommended)
import { FsAdapter, LocalStorageAdapter, EncryptedAdapter,
         BunSQLiteAdapter, D1Adapter, LibSQLAdapter }       from 'skalex/connectors/storage';
import { OpenAIEmbeddingAdapter, OllamaEmbeddingAdapter }   from 'skalex/connectors/embedding';
import { OpenAILLMAdapter, AnthropicLLMAdapter,
         OllamaLLMAdapter }                                 from 'skalex/connectors/llm';
// Or pull everything from the root barrel
import { FsAdapter, OpenAIEmbeddingAdapter, OpenAILLMAdapter } from 'skalex/connectors';

IIFE - exposes window.Skalex, for quick demos or environments that can't use ESM:

<!-- jsDelivr (recommended) -->
<script src="https://cdn.jsdelivr.net/npm/skalex@4.0.0-alpha.1"></script>

<!-- unpkg -->
<script src="https://unpkg.com/skalex@4.0.0-alpha.1"></script>

Quick Start - 30 seconds to a working database

import Skalex from "skalex";

const db = new Skalex({ path: "./data", format: "json" });
await db.connect();

const users = db.useCollection("users");

const alice    = await users.insertOne({ name: "Alice", role: "admin" });
const { docs }        = await users.find({ role: "admin" });
await users.updateOne({ name: "Alice" }, { score: { $inc: 10 } });
await users.deleteOne({ name: "Alice" });

await db.disconnect();

With Vector Search

import Skalex from "skalex";

const db = new Skalex({
  path: "./data",
  ai: { provider: "openai", apiKey: process.env.OPENAI_KEY },
});
await db.connect();

const articles = db.useCollection("articles");

await articles.insertMany([
  { title: "Intro to Skalex", content: "A zero-dependency JS database..." },
  { title: "Vector search 101", content: "Cosine similarity measures angle between vectors..." },
], { embed: "content" });

const { docs, scores } = await articles.search("how do I set up a JS database?", { limit: 2 });
console.log(docs[0].title); // most relevant result

await db.disconnect();

Documentation

Everything you need to go from zero to production:

tarekraafat.github.io/skalex :notebook_with_decorative_cover:

See what's shipping next: Roadmap

Support

• Stack Overflow: stackoverflow.com/questions/tagged/skalex
• GitHub Discussions: github.com/TarekRaafat/skalex/discussions

Author

Tarek Raafat

• Email: tarek.m.raafat@gmail.com
• Github: github.com/TarekRaafat

License

Released under the Apache 2.0 license.

© 2026 Tarek Raafat