Skillget

kodit

mcp
Guvenlik Denetimi
Gecti
Health Gecti
  • License — License: Apache-2.0
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 117 GitHub stars
Code Gecti
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This tool is an MCP server that indexes external and local code repositories. It allows AI coding assistants to search for and retrieve relevant code snippets to improve code generation accuracy and reduce hallucinations.

Security Assessment
The overall risk is Low. The server operates as a specialized search engine, cloning external Git repositories and indexing local directories to expose relevant code to your AI assistant. While this inherently involves reading source code and making network requests to fetch repositories, the automated code scan found no hardcoded secrets or dangerous patterns. It explicitly respects `.gitignore` and `.noindex` files, ensuring it does not accidentally expose sensitive local files.

Quality Assessment
The project appears to be highly maintained and professional. It is written in Go, has clear and comprehensive documentation, and saw repository activity as recently as today. It is protected by the standard Apache-2.0 license. With over 100 GitHub stars, the tool demonstrates a solid baseline of community trust and active usage among developers.

Verdict
Safe to use.
SUMMARY

👩‍💻 MCP server to index external repositories

README.md

Helix Kodit Logo

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.

Documentation
License
Discussions

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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 fewer 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 20+ programming languages including Python, JavaScript/TypeScript, Java, Go, Rust, C/C++, C#, HTML/CSS, and more
  • Advanced code analysis 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
  • Auto-indexing configuration for shared server deployments
  • Enhanced Git provider support including Azure DevOps
  • Index private repositories via a PAT
  • Improved progress monitoring and reporting during indexing
  • Advanced code slicing infrastructure with Tree-sitter parsing
  • Automatic periodic sync to keep indexes up-to-date

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 ...
  • Advanced search filters by source, language, author, date range, and file path
  • Hybrid search combining BM25 keyword search with semantic search
  • Enhanced MCP tools with rich context parameters and metadata

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:

Supported providers:

  • Local (which uses tiny CPU-only open-source models)
  • OpenAI
  • Secure, private LLM enclave with Helix.
  • Any other OpenAI compatible API

Enhanced deployment options:

  • Docker Compose configurations with VectorChord
  • Kubernetes manifests for production deployments

Quick Start

  1. Install Kodit
  2. Index codebases
  3. Integrate with your coding assistant

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

Apache 2.0 © 2026 HelixML, Inc.

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