Kodit
What is Kodit
Kodit is a tool designed to enhance AI coding capabilities by providing better context for developers, facilitating improved coding practices and productivity.
Use cases
Use cases for kodit include automating repetitive coding tasks, providing contextual code suggestions, and enhancing collaborative coding efforts among teams.
How to use
Kodit can be installed using various methods including Docker, pipx, Homebrew, uv, or pip. Each method installs the kodit CLI, which includes the kodit MCP server and tools for managing data sources.
Key features
Key features of kodit include a command-line interface for easy access, support for multiple installation methods, and the ability to function as a Python library for integration into existing projects.
Where to use
Kodit is suitable for software development environments, particularly where AI-assisted coding is beneficial, such as in startups, tech companies, and educational institutions focused on programming.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Kodit
Kodit is a tool designed to enhance AI coding capabilities by providing better context for developers, facilitating improved coding practices and productivity.
Use cases
Use cases for kodit include automating repetitive coding tasks, providing contextual code suggestions, and enhancing collaborative coding efforts among teams.
How to use
Kodit can be installed using various methods including Docker, pipx, Homebrew, uv, or pip. Each method installs the kodit CLI, which includes the kodit MCP server and tools for managing data sources.
Key features
Key features of kodit include a command-line interface for easy access, support for multiple installation methods, and the ability to function as a Python library for integration into existing projects.
Where to use
Kodit is suitable for software development environments, particularly where AI-assisted coding is beneficial, such as in startups, tech companies, and educational institutions focused on programming.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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 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 a variety of local and 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 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
- Privacy first: respects .gitignore and .noindex files.
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:
- 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. Everything
can even run securely, privately, with on-premise LLM platforms like
Helix.
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
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
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
