# KALKI 1 5 > KALKI AI (Krishna Artificial Lattice Keystone Intelligence) is an Enterprise Intelligence Operating System (IOS) combining LLMs, VLMs, autonomous multi-agents, hybrid RAG, and defensive cybersecurity. - **Type:** MCP server - **Install:** `agentstack add mcp-kgupta171025-kalki-1-5` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [KGupta171025](https://agentstack.voostack.com/s/kgupta171025) - **Installs:** 0 - **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [KGupta171025](https://github.com/KGupta171025) - **Source:** https://github.com/KGupta171025/KALKI-1.5 ## Install ```sh agentstack add mcp-kgupta171025-kalki-1-5 ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # KALKI AI — Krishna Artificial Lattice Keystone Intelligence Next-Generation Enterprise Intelligence Operating System (IOS) --- ## 🌟 Executive Summary **KALKI AI** (**Krishna Artificial Lattice Keystone Intelligence**) is a next-generation, unified artificial intelligence ecosystem engineered to operate as a full **Intelligence Operating System (IOS)**. Designed for cloud, desktop, mobile, smartwatch, and edge IoT devices, KALKI AI brings together Large Language Models (LLMs), Vision-Language Models (VLMs), Small Language Models (SLMs), Mixture-of-Experts (MoE) task routing, multi-agent orchestration (via Model Context Protocol and Agent-to-Agent IPC), hybrid RAG search, hierarchical memory, and defensive cybersecurity safeguards. --- ## 🏗️ 7-Layer System Architecture Blueprint ``` +-----------------------------------------------------------------------+ | LAYER 1: USER INTERFACE LAYER | | Web (Next.js) | Mobile (Flutter) | Desktop (Tauri) | Smartwatch | API| +-----------------------------------------------------------------------+ | LAYER 6: SECURITY & GOVERNANCE LAYER (Perimeter & In-Line Audit) | | OAuth2 / MFA | RBAC Control | AES-256 E2EE | AI Safety & Defense | +-----------------------------------------------------------------------+ | LAYER 2: MULTIMODAL PERCEPTION LAYER | | Text & PDF Parsing | OCR & Scene VLM | Whisper Audio | Sensor Stream | +-----------------------------------------------------------------------+ | LAYER 4: AGENT ORCHESTRATION LAYER | | Planner | Research | Memory | Executor | Validator | Security | | Standard Protocols: MCP (Model Context Protocol) & A2A Inter-Agent | +-----------------------------------------------------------------------+ | LAYER 3: REASONING & MODEL LAYER | | MoE Task Router | LLM Cluster | Edge SLMs (INT4) | LCM Conversational| +-----------------------------------------------------------------------+ | LAYER 5: KNOWLEDGE & RAG LAYER | | Dense Vector + BM25 Sparse | Cross-Encoder Re-Ranker | Neo4j KG | +-----------------------------------------------------------------------+ | LAYER 7: INFRASTRUCTURE LAYER | | Kubernetes (EKS/GKE) | Docker Compose | Edge Runtime | Prometheus | +-----------------------------------------------------------------------+ ``` --- ## 🚀 Key Features & Capabilities - **Ultra-Fast Performance**: End-to-end response latency budget targeted under **<500ms**, with hybrid RAG retrieval **<200ms**. - **Autonomous Multi-Agent Orchestration**: Specialized Planner, Research, Memory, Executor, Validator, and Security agents communicating via **MCP** and **A2A**. - **Hierarchical Memory System**: Short-term context, Long-term user preferences, Semantic embeddings, Episodic history, and Procedural DAG patterns. - **Hybrid RAG Engine**: Reciprocal Rank Fusion (RRF) combining dense vector search and BM25 sparse keyword indexing with Cross-Encoder re-ranking. - **Defensive Cybersecurity**: Built-in security audit tools, SAST/DAST compliance reporting, anomaly detection, and strict safety guardrails. - **Edge AI Deployment**: Quantized INT4 SLMs capable of running offline on mobile and IoT devices. --- ## 📚 Technical Documentation Index Detailed blueprints and specifications are available in the [`docs/`](./docs/) directory: - 📐 **[System Architecture Blueprint](./docs/ARCHITECTURE.md)** — Comprehensive 7-layer design & latency budget. - 🗄️ **[Database & Memory Schema](./docs/DATABASE_SCHEMA.sql)** — PostgreSQL relational schema & vector indexes. - 🌐 **[API Specification](./docs/API_SPECIFICATION.yaml)** — OpenAPI 3.0 specs for Gateway, Agents, RAG, and Security. - 🤖 **[Multi-Agent Protocols](./docs/AGENT_PROTOCOLS.md)** — Model Context Protocol (MCP) & Agent-to-Agent (A2A) IPC. - 🔍 **[RAG Pipeline Specification](./docs/RAG_PIPELINE.md)** — Hybrid retrieval, RRF math, re-ranking, and citation model. - 🛡️ **[Security & Governance](./docs/SECURITY_AND_GOVERNANCE.md)** — RBAC matrix, E2EE, defensive cybersecurity, and HITL. - 🐳 **[Deployment & DevOps](./docs/DEPLOYMENT_AND_DEVOPS.md)** — Kubernetes manifests, Edge SLM pipeline, Prometheus metrics. - 📊 **[Business & Scalability](./docs/BUSINESS_AND_SCALABILITY.md)** — Infrastructure cost model, 10M user scaling roadmap, risk matrix. --- ## 💻 Tech Stack Overview - **Frontend**: Next.js 14, React 18, TypeScript, Tailwind CSS, Lucide Icons. - **Backend**: Python 3.11+, FastAPI, Pydantic v2, Asyncio, gRPC. - **AI & ML**: PyTorch, Hugging Face Transformers, vLLM, ONNX Runtime, llama.cpp. - **Data & Storage**: PostgreSQL (with `pgvector`), Redis, Qdrant Vector Store, Neo4j Knowledge Graph. - **DevOps**: Docker, Docker Compose, Kubernetes, Helm, Prometheus, Grafana. --- ## 🛠️ Quickstart Guide ### Prerequisites - Docker & Docker Compose - Python 3.11+ - Node.js 18+ ### 1. Running via Docker Compose ```bash # Clone the repository git clone https://github.com/KGupta171025/KALKI-1.5.git cd KALKI-1.5 # Launch full stack (FastAPI Backend, Next.js Frontend, PostgreSQL, Redis, Qdrant) docker compose up --build ``` Access services: - **Web UI Dashboard**: `http://localhost:3000` - **FastAPI OpenAPI Documentation**: `http://localhost:8000/docs` - **Qdrant Vector Dashboard**: `http://localhost:6333/dashboard` --- ## 📜 License & Governance Developed under responsible AI guidelines. Designed for authorized, ethical enterprise deployment and defensive cybersecurity monitoring. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [KGupta171025](https://github.com/KGupta171025) - **Source:** [KGupta171025/KALKI-1.5](https://github.com/KGupta171025/KALKI-1.5) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-kgupta171025-kalki-1-5 - Seller: https://agentstack.voostack.com/s/kgupta171025 - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.