codealive.dev

# CodeAlive > Context Engine for AI coding agents. Graph RAG over large multi-repo codebases, delivered via MCP for Claude Code, Cursor, and Codex. Cloud or self-hosted. CodeAlive is a Context Engine (Graph RAG) for large software codebases. It indexes source code, builds a knowledge graph over symbols, modules, and cross-repository dependencies, and exposes that index to engineers (via web chat) and to AI coding agents (via MCP and a REST API). It is purpose-built for monorepos and multi-repo systems at enterprise scale and is available as a managed cloud service or a self-hosted deployment (Docker / Kubernetes). Primary positioning: The Context Engine for AI Coding Agents on Large Codebases ## Products - [Context Engine](https://codealive.ai/en/products/context-engine): Graph RAG retrieval engine for large codebases. Hybrid symbol + semantic search delivered over MCP, REST, and IDE extensions. - [Code Review Agent](https://codealive.ai/en/products/code-review-agent): Architecture-aware code review that reads the rest of the codebase, not just the diff. Posts reviews back to GitHub / GitLab / Bitbucket pull requests. - [Deep Research](https://codealive.ai/en/products/deep-research): Multi-step reasoning over the codebase for hard architectural questions, with transparent citations back to files and lines. - [MCP & API](https://codealive.ai/en/products/mcp-api): Drop-in MCP server and REST API for Claude Code, Cursor, Codex, Continue, Cline, and any MCP-aware client. - [Self-Hosted](https://codealive.ai/en/self-hosted): On-premise deployment via Docker Compose or Kubernetes / Helm. Bring-your-own LLM (Qwen, Llama, GLM, DeepSeek, gpt-oss). ## Use Cases - [Code Review](https://codealive.ai/en/use-cases/code-review): Reviews grounded in the whole system, not just the diff. - [Onboarding](https://codealive.ai/en/use-cases/onboarding): New engineers ask the codebase questions instead of waiting on seniors. - [Feature Planning](https://codealive.ai/en/use-cases/fea