Kodit: A Code Indexing MCP Server
Kodit connects your AI coding assistant to external codebases to provide accurate and up-to-date snippets of code.
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 byproviding relevant and up-to-date examples of your task so that LLMs make less mistakesand produce fewer hallucinations.
✨ Features
Codebase Indexing
Kodit connects to a variety of local and remote codebases to build an index of yourcode. This index is used to build a snippet library, ready for ingestion into an LLM.
- Index local directories and public Git repositories
- Build comprehensive snippet libraries for LLM ingestion
- Support for multiple codebase types and languages
- Efficient indexing and search capabilities
MCP Server
Relevant snippets are exposed to an AI coding assistant via an MCP server. This allowsthe assistant to request relevant snippets by providing keywords, code, and semanticintent. Kodit has been tested to work well with:
- Seamless integration with popular AI coding assistants
- Tested and verified with:
- Please contribute more instructions! ... any other assistant is likely to work ...
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. Everythingcan even run securely, privately, with on-premise LLM platforms likeHelix.
Supported databases:
- SQLite
- Vectorchord
Supported providers:
- Local (which uses tiny CPU-only open-source models)
- OpenAI
- Secure, private LLM enclave with Helix.
- Any other OpenAI compatible API
🚀 Quick Start
Documentation
- Getting Started Guide
- Reference Guide
- Contribution Guidelines
Roadmap
The roadmap is currently maintained as a Github Project.
💬 Support
For commercial support, please contact Helix.ML. To ask a question,please open a discussion.
License
Apache 2.0 © 2025 HelixML, Inc.