llm-context

What is LLM Context?

LLM Context is a tool designed to facilitate the interaction between developers and Large Language Models (LLMs) by efficiently injecting relevant code and text content into LLM chat interfaces. It utilizes .gitignore patterns for intelligent file selection and supports both a command-line interface (CLI) for clipboard-based workflows and direct integration with LLMs via the Model Context Protocol (MCP).

How to use LLM Context?

Installation:

Install using uv:

uv tool install "llm-context>=0.3.0"

To upgrade:

uv tool upgrade llm-context

MCP with Claude Desktop:

Add the following to claude_desktop_config.json:

{
  "mcpServers": {
    "CyberChitta": {
      "command": "uvx",
      "args": ["--from", "llm-context", "lc-mcp"]
    }
  }
}

Then, you can either say "I would like to work with my project" or "I would like to work with my project /path/to/your/project" in Claude.

CLI Quick Start and Typical Workflow:

Navigate to your project's root directory.
Initialize repository: lc-init (only once).
Select files: lc-sel-files.
(Optional) Review selected files in .llm-context/curr_ctx.yaml.
Generate context: lc-context (with optional flags: -p for prompt, -u for user notes).
Use with your preferred interface (e.g., paste into knowledge section of Claude Pro, Custom GPTs, or regular chats).
When the LLM requests additional files:
- Copy the file list from the LLM.
- Run lc-clip-files.
- Paste the contents back to the LLM.

Key Features of LLM Context

Smart File Selection: Utilizes .gitignore patterns for intelligent and relevant file inclusion.
Multiple Rule-Based Profiles: Supports different use cases with system rules (prefixed with "lc-") and user-defined rules.
Code Navigation Features:
- Smart Code Outlines: Generates high-level structural outlines of your codebase for LLMs.
- Definition Implementation Extraction: Extracts full implementations of specific definitions requested by LLMs using lc-clip-implementations.
Customizable Templates and Prompts: Allows for tailored content presentation.
Direct LLM Integration: Native integration with Claude Desktop via MCP protocol.
Chat Interface Support: Works with any LLM chat interface via CLI/clipboard, optimized for persistent context interfaces.

Use Cases of LLM Context

AI-Assisted Development: Streamlines the process of sharing code with LLMs for tasks like code review, documentation generation, and debugging.
Code Understanding: Helps LLMs understand the structure and content of your codebase.
Project Context Provision: Provides relevant project context to LLMs for more accurate and helpful responses.
Diverse Project Types: Suitable for code repositories and collections of text/markdown/HTML documents.

FAQ about LLM Context

What kind of projects does LLM Context support? It supports code repositories and collections of text/markdown/HTML documents.
What project sizes are optimized for LLM Context? It is optimized for projects that fit within an LLM's context window. Support for larger projects is under development.
Is LLM Context under active development? Yes, it is under active development. Updates may overwrite configuration files prefixed with lc-, so it's recommended to version control all configuration files.
How does LLM Context handle LLM requests for additional files? You can copy the file list from the LLM, run lc-clip-files, and then paste the contents back to the LLM.
Can I customize the rules for file selection? Yes, LLM Context provides multiple rule-based profiles, including system rules and user-defined rules that can extend existing ones.

LLM Context

LLM Context is a tool that helps developers quickly inject relevant content from code/text projects into Large Language Model chat interfaces. It leverages .gitignore patterns for smart file selection and provides both a streamlined clipboard workflow using the command line and direct LLM integration through the Model Context Protocol (MCP).

Note: This project was developed in collaboration with several Claude Sonnets - 3.5, 3.6 and 3.7 (and more recently Grok-3 as well), using LLM Context itself to share code during development. All code in the repository is human-curated (by me 😇, @restlessronin).

Why LLM Context?

For an in-depth exploration of the reasoning behind LLM Context and its approach to AI-assisted development, check out our article: LLM Context: Harnessing Vanilla AI Chats for Development

To see LLM Context in action with real-world examples and workflows, read: Full Context Magic - When AI Finally Understands Your Entire Project

Current Usage Patterns

Direct LLM Integration: Native integration with Claude Desktop via MCP protocol
Chat Interface Support: Works with any LLM chat interface via CLI/clipboard
- Optimized for interfaces with persistent context like Claude Projects and Custom GPTs
- Works equally well with standard chat interfaces
Project Types: Suitable for code repositories and collections of text/markdown/html documents
Project Size: Optimized for projects that fit within an LLM's context window. Large project support is in development

Installation

Install LLM Context using uv:

uv tool install "llm-context>=0.3.0"

To upgrade to the latest version:

uv tool upgrade llm-context

Warning: LLM Context is under active development. Updates may overwrite configuration files prefixed with lc-. We recommend all configuration files be version controlled for this reason.

Quickstart

MCP with Claude Desktop

Add to 'claude_desktop_config.json':

{
  "mcpServers": {
    "CyberChitta": {
      "command": "uvx",
      "args": ["--from", "llm-context", "lc-mcp"]
    }
  }
}

Once configured, you can start working with your project in two simple ways:

Say: "I would like to work with my project" Claude will ask you for the project root path.
Or directly specify: "I would like to work with my project /path/to/your/project" Claude will automatically load the project context.

Preferred Workflow: Combining Project UI with MCP

For optimal results, combine initial context through Claude's Project Knowledge UI with dynamic code access via MCP. This provides both comprehensive understanding and access to latest changes. See Full Context Magic for details and examples.

CLI Quick Start and Typical Workflow

Navigate to your project's root directory
Initialize repository: lc-init (only needed once)
Select files: lc-sel-files
(Optional) Review selected files in .llm-context/curr_ctx.yaml
Generate context: lc-context (with optional flags: -p for prompt, -u for user notes)
Use with your preferred interface:

Project Knowledge (Claude Pro): Paste into knowledge section
GPT Knowledge (Custom GPTs): Paste into knowledge section
Regular chats: Use lc-context -p to include instructions

When the LLM requests additional files:
- Copy the file list from the LLM
- Run lc-clip-files
- Paste the contents back to the LLM

Core Commands

lc-init: Initialize project configuration
lc-set-rule <n>: Switch rules (system rules are prefixed with "lc-")
lc-sel-files: Select files for inclusion
lc-sel-outlines: Select files for outline generation
lc-context [-p] [-u] [-f FILE]: Generate and copy context
- -p: Include prompt instructions
- -u: Include user notes
- -f FILE: Write to output file
lc-prompt: Generate project instructions for LLMs
lc-clip-files: Process LLM file requests
lc-changed: List files modified since last context generation
lc-outlines: Generate outlines for code files
lc-clip-implementations: Extract code implementations requested by LLMs (doesn't support C/C++)

Features & Advanced Usage

LLM Context provides advanced features for customizing how project content is captured and presented:

Smart file selection using .gitignore patterns
Multiple rule-based profiles for different use cases
- System rules (prefixed with "lc-") provide default functionality
- User-defined rules can be created independently or extend existing rules
Code Navigation Features:
1. Smart Code Outlines: Allows LLMs to view the high-level structure of your codebase with automatically generated outlines highlighting important definitions
2. Definition Implementation Extraction: Paste full implementations of specific definitions that are requested by LLMs after they review the code outlines, using the lc-clip-implementations command
Customizable templates and prompts

See our User Guide for detailed documentation of these features.

Similar Tools

Check out our comprehensive list of alternatives - the sheer number of tools tackling this problem demonstrates its importance to the developer community.

Acknowledgments

LLM Context evolves from a lineage of AI-assisted development tools:

This project succeeds LLM Code Highlighter, a TypeScript library I developed for IDE integration.
The concept originated from my work on RubberDuck and continued with later contributions to Continue.
LLM Code Highlighter was heavily inspired by Aider Chat. I worked with GPT-4 to translate several Aider Chat Python modules into TypeScript, maintaining functionality while restructuring the code.
This project uses tree-sitter tag query files from Aider Chat.
LLM Context exemplifies the power of AI-assisted development, transitioning from Python to TypeScript and back to Python with the help of GPT-4 and Claude-3.5-Sonnet.

I am grateful for the open-source community's innovations and the AI assistance that have shaped this project's evolution.

I am grateful for the help of Claude-3.5-Sonnet in the development of this project.

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.

llm-context Overview