Kodit

--- title: "Kodit: Code Indexing MCP Server" linkTitle: Kodit Docs cascade: type: docs menu: main: name: Kodit Docs weight: 3 next: /kodit/getting-started weight: 1 aliases: - /coda --- <p align="center"> <a href="https://docs.helix.ml/kodit/"><img src="https://docs.helix.ml/images/helix-kodit-logo.png" alt="Helix Kodit Logo" width="300"></a> </p> <p align="center"> Kodit connects your AI coding assistant to external codebases to provide accurate and up-to-date snippets of code. </p> <div class="flex justify-center items-center gap-4"> [](https://github.com/helixml/kodit/blob/main/LICENSE) [](https://github.com/helixml/kodit/discussions) </div> **Helix Kodit** is an **MCP server** that connects your AI coding assistant to external codebases. It can: - Improve your AI-assisted code by providing canonical examples direct from the source - Index local and public codebases - Integrates with any AI coding assistant via MCP - Search using keyword and semantic search - Integrate with any OpenAI-compatible or custom API/model If you're an engineer working with AI-powered coding assistants, Kodit helps by providing relevant and up-to-date examples of your task so that LLMs make less mistakes and produce fewer hallucinations. ## Features ### Codebase Indexing Kodit connects to remote codebases to build an index of your code. This index is used to build a snippet library, ready for ingestion into an LLM. - Index public and private Git repositories (via a PAT) - Build comprehensive snippet libraries for LLM ingestion - Support for 20+ programming languages including Python, JavaScript/TypeScript, Java, Go, Rust, C/C++, C#, HTML/CSS, and more - Advanced code slicing with dependency tracking and call graph generation - Intelligent snippet extraction with context-aware dependencies - Efficient indexing with selective reindexing (only processes modified files) - Privacy first: respects .gitignore and .noindex files - Enhanced Git provider support including Github, Gitlab, Azure DevOps - **New in 0.5**: Index Git structure for incremental indexing and unlock future enrichments ### MCP Server Relevant snippets are exposed to an AI coding assistant via an MCP server. This allows the assistant to request relevant snippets by providing keywords, code, and semantic intent. Kodit has been tested to work well with: - Seamless integration with popular AI coding assistants - Tested and verified with: - [Cursor](./reference/mcp/index.md) - [Cline](./reference/mcp/index.md) - [Claude Code](./reference/mcp/index.md) - Please contribute more instructions! ... any other assistant is likely to work ... - Advanced search filters by source, language, author, date range, and file path - Hybrid search combining BM25 keyword search with semantic search ### Hosted MCP Server Try Kodit instantly with our hosted MCP server at [https://kodit.helix.ml/mcp](https://kodit.helix.ml/mcp)! No installation required - just add it to your AI coding assistant and start searching popular codebases immediately. The hosted server provides: - Pre-indexed popular open source repositories - Zero configuration - works out of the box - Same powerful search capabilities as self-hosted Kodit - Perfect for trying Kodit before setting up your own instance Read the [hosted Kodit documentation](./reference/hosted-kodit/index.md). ### Enterprise Ready Out of the box, Kodit works with a local SQLite database and very small, local models. But enterprises can scale out with performant databases and dedicated models. Everything can even run securely, privately, with on-premise LLM platforms like [Helix](https://helix.ml). Supported databases: - SQLite - [Vectorchord](https://github.com/tensorchord/VectorChord) Supported providers: - Local (which uses tiny CPU-only open-source models) - Secure, private LLM enclave with [Helix](https://helix.ml). - Any other provider supported by [LiteLLM](https://docs.litellm.ai/docs/providers). - Docker Compose configurations with VectorChord - Kubernetes manifests for production deployments ## Roadmap The roadmap is currently maintained as a [Github Project](https://github.com/orgs/helixml/projects/4). ## 💬 Support For commercial support, please contact [Helix.ML](https://docs.helixml.tech/helix/help/). To ask a question, please [open a discussion](https://github.com/helixml/kodit/discussions). ## License [Apache 2.0 © 2025 HelixML, Inc.](https://github.com/helixml/kodit/blob/main/LICENSE)