smaran

<div align="center"> <img src="apps/web/public/logo.png" width="500" alt="Smaran Logo" /> <br /> <br /> <p> <b>The Intelligent Memory Backend for AI Agents</b> </p> <p> <a href="https://smaran.ai"><img src="https://img.shields.io/badge/Website-smaran.ai-orange.svg" alt="Website" /></a> <a href="https://github.com/Ayushpani/engram/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-Proprietary-blue.svg" alt="License" /></a> <img src="https://img.shields.io/badge/Status-Closed_Beta-success.svg" alt="Beta" /> <img src="https://img.shields.io/badge/Platform-Cloudflare_Edge-orange.svg" alt="Platform" /> </p> </div> --- ## What is Smaran? Smaran is a state-of-the-art memory infrastructure layer designed from the ground up for AI agents. It acts as the ultimate long-term memory engine for agents like **Claude Desktop**, **Cursor**, and custom LLM workflows, allowing them to instantly recall your knowledge with perfect context. Traditional Retrieval-Augmented Generation (RAG) systems suffer from "context bloat"—repeated facts, messy data, and degraded LLM reasoning. **Smaran solves this.** When you plug Smaran into your agent, it acts as a hyper-intelligent brain: intercepting raw context, filtering duplicates mathematically on the client side, and executing millisecond edge-side reranking before serving only the highest-quality, distilled facts back to the LLM. --- ## Core Features * **Edge Reranking via Cloudflare Workers AI**: Employs a blazing-fast Cross-Encoder (`@cf/baai/bge-reranker-base`) directly at the network edge, ensuring low-latency intelligence routing. * **Client-Side WASM Deduplication**: Filters exact and near-exact duplicates *before* network transport using an ultra-fast WebAssembly port of the `all-MiniLM-L6-v2` model. * **Graph-Based Consolidation**: Uses the Louvain Modularity algorithm compiled to WASM to detect dense clusters in your memory space, automatically synthesizing messy notes into unified facts. * **Universal MCP Integration**: Connects effortlessly to Claude Desktop via the standard Model Context Protocol (MCP). --- ## Getting Started ### 1. Get an API Key (Closed Beta) Smaran is currently in a strict closed beta to ensure we provide a premium, high-quality onboarding experience. **[Join the waitlist at smaran.ai](https://smaran.ai)** to request access. We review every request personally and will email you an API key if you're a good fit. ### 2. Test the Edge Reranker Locally (No API Key Required) If you want to witness the power of our Cloudflare Edge Reranker right now without an API key, we have provided a mocked End-to-End test script. This script intercepts a core API call, mocks 50 messy baseline memories, and pipes them directly to the live Smaran Edge Reranker Worker. ```bash # 1. Install dependencies across the monorepo bun install # 2. Run the E2E test script cd apps/mcp bun run test-mcp-e2e.ts ``` *Watch your terminal as the Cloudflare Worker rescues the target memory from the absolute bottom of the pile (position 43) all the way up to position 1.* ### 3. Connect to Claude Desktop (Requires API Key) Once you have secured your API key, you can give Claude Desktop a perfect memory using our Model Context Protocol (MCP) server. 1. **Start the local MCP server:** ```bash cd apps/mcp npx wrangler dev --port 8788 ``` 2. **Configure Claude Desktop:** Open your Claude configuration file (`claude_desktop_config.json`) and register the Smaran server: ```json { "mcpServers": { "smaran": { "command": "npx", "args": ["@modelcontextprotocol/inspector", "http://127.0.0.1:8788/mcp"] } } } ``` *(Note: Because OAuth proxying is currently limited in some MCP clients, manual authentication via the inspector may be required on your first run.)* --- ## Architecture & Repository Structure Smaran is built as a high-performance **Turbo Monorepo**, separating core math engines, cloud infrastructure, and client applications. ### Applications (`apps/`) * **`web`**: The primary Smaran dashboard and landing page (Next.js). * **`mcp`**: The Model Context Protocol server, deployed on Cloudflare Workers for global low latency. * **`reranker-worker`**: The specialized Cloudflare Worker executing the BAAI Cross-Encoder model. * **`browser-extension` & `raycast-extension`**: Frontend tools for capturing context directly into your Smaran graph. ### Core Packages (`packages/`) * **`client-dedup-wasm`**: Rust-compiled WebAssembly engine for zero-latency client-side duplication filtering. * **`memory-consolidator`**: Rust-compiled Louvain Modularity engine for graph clustering. * **`benchmark`**: Automated testing harness for evaluating RAG retrieval accuracy. * **`tools`**: Built-in integrations for Slack, Notion, Google Drive, and OneDrive. --- ## Manual Build Instructions If you are contributing to the core mathematical WASM packages, you will need to compile them manually: 1. **Install the Rust Toolchain** (Ensure the `wasm32-unknown-unknown` target is installed). 2. **Build the WASM packages:** ```bash cd packages/wasm-math wasm-pack build --target bundler --release cd ../memory-consolidator wasm-pack build --target bundler --release ``` --- ## License & Copyright Smaran is proprietary software. All rights reserved. For inquiries, contact [ayush@smaran.ai](mailto:ayush@smaran.ai).