Platform binary for @dayone/cli (Linux arm64, no embeddings)

Platform binary for @dayone/cli (Linux x64, no embeddings)

Digital brain as skills for AI coding CLIs — no vector DB, no embeddings, no infrastructure

Platform binary for @dayone/cli (macOS x64, no embeddings)

Self-maintaining codebase memory for AI coding agents: an AST index that answers which files matter, plus agent-written notes that flag themselves stale when the code changes. No embeddings, no API key. CLI + MCP.

Auto-generate code metadata sidecars for LLM-optimized navigation. No AST dumps, no embeddings — just structured YAML.

Cut LLM API costs 60–90% in 3 lines of code. Semantic cache with BM25+ fuzzy matching, persistent sessions, AI memory adapter. Works with OpenAI, Anthropic, LangChain, Vercel AI SDK. No embeddings required for basic caching.

Model-agnostic code memory MCP server. Budget-aware graph retrieval for AI agents — sub-millisecond queries, token budgeting, no embeddings, no API keys. Built on CodeGraphContext for 155-language tree-sitter indexing.

Grounded GitHub repo discovery MCP server — live keyword search, no embeddings, no backend.

Geometric memory for AI coding agents. No embeddings, no vectors, no cloud - just math.

Isomorphic storage client for Supabase.

Vector-free memory for AI agents. A memory is one attention-aligned context document that is always fully in the prompt — no embeddings, no retrieval. Facts are distilled, importance-scored, and evicted by importance when the budget fills.

Sanity CLI tool for managing Sanity projects and organizations

Portable WASM embedding generation with SIMD and parallel workers - run text embeddings in browsers, Cloudflare Workers, Deno, and Node.js

SAP Fiori documentation indexing

Memory for AI agents in one line. Auto-compression, semantic recall, prompt-ready context. No embeddings, no vector DB, no setup. Zero dependencies.

pgvector support for Node.js, Deno, and Bun (and TypeScript)

Common utilities for ChromaDB AI embedding packages

Various Sanity Studio plugins for integrating with the embeddings index API

V3 Embedding Service - OpenAI, Transformers.js, Agentic-Flow (ONNX), Mock providers with hyperbolic embeddings, normalization, and chunking