Jinni: Bring Your Project Into Context

Name: Jinni: Bring Your Project Into Context
Author: smat-dev

@smat-dev

Repository

About Jinni: Bring Your Project Into Context

Bring your project into LLM context - tool and MCP server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "jinni": {
      "command": "uvx",
      "args": [
        "jinni-server",
        "[OPTIONS]"
      ]
    }
  }
}

Tools

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Comments

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