Memori Labs announced the launch of its TypeScript SDK (@memorilabs/memori), extending its SQL-native memory infrastructure to the TypeScript/Node.js ecosystem. This launch is timed with TypeScript becoming the most-used language on GitHub, driven by its suitability for AI tooling. The new SDK enables TypeScript developers to add persistent, intelligent memory to AI agents and copilots, addressing issues like token bloat and inconsistent user experiences that result from stateless LLM calls. It works as a lightweight middleware layer, wrapping existing LLM client libraries (OpenAI, Anthropic, Google Gemini) to automatically handle memory capture and recall without requiring developers to provision a new database or build an embedding pipeline.
SAN FRANCISCO, March 10, 2026 /PRNewswire-PRWeb/ -- In celebration of TypeScript surpassing both Python and JavaScript to become the most-used language on GitHub, growing 66% year-over-year according to GitHub's Octoverse 2025 report, Memori Labs today announced the launch of its TypeScript SDK (\`@memorilabs/memori\`), extending its SQL-native memory infrastructure to the language ecosystem now at the center of modern AI development.
The new SDK enables TypeScript and Node.js developers to add persistent, intelligent memory to AI agents and copilots using the same Memori Cloud platform trusted by production teams building on Python. With over 1.1 million public repositories on GitHub now using LLM SDKs, the demand for production-grade memory infrastructure in TypeScript has never been higher.
Memori Labs is the creator of the leading SQL-native memory layer for AI applications. It is one of the top-ranked memory systems, with rapidly expanding developer adoption across customer support agents, commerce automation, internal copilots, and multi-session AI workflows. With the TypeScript SDK, Memori now serves the two largest language ecosystems in AI development: Python and JavaScript under a unified API and memory platform.
"TypeScript didn't just grow. It became the number one language on GitHub, and that shift is being driven by AI," said Adam B. Struck, CEO and Co-Founder of Memori Labs. "Developers are choosing TypeScript because strongly typed languages give AI tooling clearer constraints and more reliable code generation. As that ecosystem explodes, those teams need memory infrastructure that matches the maturity of what Python developers have had. This launch delivers exactly that, production-grade memory capture, structured knowledge extraction, and intelligent recall for the language that is now leading AI development on the world's largest code platform."
Built for the Way TypeScript Developers Work
TypeScript's rise to the top of GitHub's language rankings is not incidental. As GitHub's Octoverse report notes, developer choice is shifting toward technologies that work best with AI tooling. TypeScript's strong type system gives AI models clearer constraints for more reliable code generation. But while the language ecosystem has matured rapidly, most AI applications built in TypeScript today still rely on stateless LLM calls, forcing developers to manually reconstruct context with every interaction. This leads to token bloat, higher inference costs, and inconsistent user experiences, problems that compound as applications scale to thousands of users and sessions.
The Memori TS SDK eliminates this by wrapping existing LLM client libraries (OpenAI, Anthropic, and Google Gemini) with a lightweight middleware layer that automatically handles memory capture, advanced augmentation, and intelligent recall. Developers register their LLM client, set attribution, and Memori handles the rest. There is no new database to provision, no embedding pipeline to build, and no retrieval logic to maintain.
What the TypeScript SDK Delivers at Launch
The TypeScript SDK provides the full Memori Cloud memory pipeline, including:
- Synchronous capture of LLM conversations on the request path
- Async advanced augmentation to extract facts, preferences, skills, and relationships
- Intelligent recall that ranks and injects relevant memories into future prompts
- Three-tier attribution system scoping memory at the entity, process, and session levels
- Knowledge graph construction from extracted semantic triples
"When TypeScript became the most-used language on GitHub, it validated what we were already seeing from our community: the center of gravity for AI development is shifting, and developers in that ecosystem need memory infrastructure that just works," said Michael Montero, CTO of Memori Labs. "We designed the TypeScript SDK to feel native to the ecosystem, not like a port of a Python library. Developers register their existing OpenAI, Anthropic, or Gemini client in a single line and get automatic conversation capture, advanced augmentation, and intelligent recall. The integration is three lines of code and the underlying architecture handles synchronous persistence, asynchronous fact extraction, and semantic retrieval without adding latency to the request path."
Unified Platform Across Python and TypeScript
The TypeScript SDK joins Memori's established Python SDK, which has served as the foundation for production AI applications across enterprises. Both SDKs share the same API design philosophy and connect to the same Memori Cloud platform, ensuring a consistent developer experience and unified memory store across language ecosystems.
Teams running multi-language architectures such as a Python-based data pipeline feeding a TypeScript-based customer-facing agent, can now share the same memory infrastructure and attribution model across their entire stack.
The Python SDK additionally supports Memori BYODB (Bring Your Own Database) mode with native adapters for PostgreSQL, MySQL, MongoDB, SQLite, CockroachDB, Oracle, and more, thereby giving enterprises full data ownership and compliance control. Memori BYODB support for the TypeScript SDK is on the roadmap.
Full Observability Through the Cloud Dashboard
Teams using the TS SDK get the same Memori Cloud tooling available to Python users, including:
Memories inspect memory rows, subjects, retrieval counts, and graph relationships
Analytics monitor created and recalled volume, sessions, users, and quota usage
Playground chat and watch extracted memories and graph updates in real time
Availability
The Memori TypeScript SDK is available immediately on npm (\`npm install @memorilabs/memori\`). Teams can begin building memory-native AI systems today by signing up for a free API key at app.memorilabs.ai. Enterprise plans with dedicated support, higher throughput, and SLA guarantees are available by contacting the Memori Labs team.
About Memori Labs
Memori Labs builds SQL-native memory infrastructure for LLM applications, agents, and copilots. The platform continuously captures interactions, extracts structured knowledge, and intelligently ranks, decays, and retrieves relevant memory \- enabling AI systems to remember the right things at the right time across every session.
Memori Labs offers Memori Cloud, a fully managed platform for rapid deployment, as well as flexible enterprise deployment options including Memori, BYODB (Bring Your Own Database), VPC, and on-prem configurations for organizations that require full infrastructure control, security, and compliance alignment.
Media Contact
Amandeep Sandhu, Memori Labs, 1 4157137321, [email protected], www.memorilabs.ai
SOURCE Memori Labs
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