概览
What is Jinni: Bring Your Project Into Context?
Jinni is a tool for developers to efficiently provide Large Language Models with a consolidated view of relevant project files. It integrates with AI tools via an MCP (Model Context Protocol) server and offers a command-line utility for manual copy-paste or file output.
How to use Jinni: Bring Your Project Into Context?
Configure your MCP client to run the server via uvx jinni-server, or use the CLI directly with jinni [OPTIONS] [<PATH...>]. The MCP server exposes the read_context tool; the CLI outputs concatenated file contents to stdout or clipboard.
Key features of Jinni: Bring Your Project Into Context
- Efficient consolidation of relevant project files.
- Intelligent filtering using gitignore-style patterns.
- Customizable inclusions via
.contextfiles. - Configurable size limit for large contexts.
- File path headers in output.
- List-only mode for file preview.
Use cases of Jinni: Bring Your Project Into Context
- Integrating with AI coding assistants like Cursor or Claude Desktop.
- Quickly providing project context to an LLM for code generation.
- Focusing LLM attention on specific modules or file patterns.
- Debugging large projects by excluding irrelevant directories.
- Generating a structured text dump for offline LLM analysis.
FAQ from Jinni: Bring Your Project Into Context
What runtime does Jinni require?
Jinni requires uv to run the MCP server via uvx jinni-server. The CLI is also available as jinni and can be run directly.
How does Jinni decide which files to include?
It uses built-in defaults that exclude binaries, dotfiles, and common temp/build directories. It also respects .gitignore rules and allows custom inclusions via .contextfiles
