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LLMScribe
v1.1.0 on PyPI
MCP Server Built-in
Standalone EXE
Apache 2.0

Give any project to an AI in seconds.

Turn any project folder into clean, structured context for AI agents & developers. Zero configuration. Built for AI agents, terminal power users, and non-technical desktop users.

pip install llmscribe
Get startedView source

Four ways to run: llmscribe-mcp, LLMScribe-GUI.exe, llmscribe, llmscribe-cui

LLMScribe

v1.0.0
Preview—

Select a project folder and press Generate. The output will appear here.

Interactive demo — Generate, copy, or download a sample export.

How it works

One walk through the tree. One file out.

  1. 01

    Point it at a folder

    Pass a path on the command line, pick a folder in the desktop window, or type it into the terminal menu. That is the only input.

  2. 02

    It walks, filters, and writes

    LLMScribe builds a directory tree, skips junk and .gitignore matches, and concatenates every supported source file into one document.

  3. 03

    Paste it into an AI chat

    The .txt is ready for ChatGPT, Claude, Grok, Cursor, or anything else that can read a project as text. Copy, open, or save it wherever you like.

Made for people who just want to give their whole project to an AI without fighting with copy-paste.

Four interfaces

An MCP server for agents, a standalone EXE, a desktop GUI, and a CLI.

Install once. Use whichever fits the situation — MCP server for AI agents, standalone EXE for non-tech users, recommended Python GUI for desktop users, CLI for terminal power users.

llmscribe-mcp (For AI Agents)

Model Context Protocol (MCP) server providing 7 tools for AI coding tools (Cursor, Claude Desktop, Windsurf, Roo Code, Goose).

Provides project_overview, project_map, project_search, project_list_files, project_get_file, project_get_files, and project_diff.

{
  "mcpServers": {
    "llmscribe": {
      "command": "llmscribe-mcp"
    }
  }
}

Output formats

Clean Markdown for humans, structured JSON for agents.

Choose Markdown mode for pasting into chat prompts, or JSON mode for programmatic agent parsing with metadata.

project_overview.txt
Selected Files Directory Structure:

my-project/
├── src/
│   ├── main.py
│   └── utils.py
├── tests/
│   └── test_main.py
├── pyproject.toml
└── README.md

File Contents:

--- src/main.py ---
def hello():
    print("Hello world")

--- src/utils.py ---
def add(a: int, b: int) -> int:
    return a + b

--- tests/test_main.py ---
from src.main import hello

def test_hello():
    hello()

--- pyproject.toml ---
[project]
name = "my-project"
version = "1.1.0"
requires-python = ">=3.10"

--- README.md ---
# my-project

A sample project exported with LLMScribe.

Capabilities

Built to give AI agents & developers predictable context.

MCP Server for AI Agents

Built-in Model Context Protocol server featuring 7 composable tools (overview, map, search, batch file read, and git diff) with structured JSON envelopes.

Git Status & Diff

Inspect modified files and unified diffs directly via project_diff tool, supporting staged, unstaged, and specific commit comparisons.

Four Interfaces

MCP server for agents, standalone Windows EXE for non-tech users, modern CustomTkinter GUI, and CLI/CUI for terminal power users.

Smart Ignore Rules

Drops .git, node_modules, venv, build caches, IDE folders, OS junk, and anything listed in the project's own .gitignore.

Deterministic Size Guards

Enforces 50-file batch caps, 400k character content limits, 200k diff character caps, and 13 closed, standardized error codes.

Embeddable Python Core

Import llmscribe.core or llmscribe.mcp from Python. Use run(), build_project_summary(), or project_overview() programmatically.

Supported Text Files

Common source code, configuration, scripts, and text extensions.

  • .py
  • .js
  • .ts
  • .jsx
  • .tsx
  • .java
  • .go
  • .rs
  • .md
  • .json
  • .yaml
  • .toml
  • .html
  • .css
  • .sh
  • .sql
  • + many more

Ignored Automatically

Dependencies, build outputs, IDE config, binary assets, and your .gitignore.

  • .git
  • node_modules
  • venv
  • __pycache__
  • dist
  • build
  • .idea
  • .vscode
  • .DS_Store
  • Thumbs.db
  • .gitignore rules

Install

Available on PyPI or Standalone EXE.

Install from PyPI using Python 3.10+, or download the pre-compiled LLMScribe-GUI.exe from GitHub Releases.

From PyPI
pip install llmscribe
From source
git clone https://github.com/AMRITO-KUNDU/LLMScribe.git
cd LLMScribe
pip install -e .
Build Standalone EXE
# Build standalone LLMScribe-GUI.exe:
pip install pyinstaller
python build_exe.py

Generates dist/LLMScribe-GUI.exe (PyInstaller executable for non-tech users).

llmscribe-mcp
MCP server for AI agents in Cursor & Claude.
LLMScribe-GUI.exe
Standalone desktop app (no Python needed).
llmscribe
Command-line tool for fast path exports.
llmscribe-cui
Numbered terminal menu.

Python API

Use the core from your own code.

The same writer the CLI uses is importable. Write a file, or keep the summary as a string and send it wherever you need context.

llmscribe.core.writer
from pathlib import Path
from llmscribe.core.writer import run, build_project_summary
from llmscribe.mcp import project_overview, project_diff

# 1. Direct Python Core Usage
text = build_project_summary(Path("/path/to/project"))

# 2. Call MCP tools programmatically (JSON mode or Markdown)
json_overview = project_overview("/path/to/project", format="json")
diff_markdown = project_diff("/path/to/project", staged=False)

FAQ

Common questions

Stop copying files one at a time.

Install LLMScribe, point it at a project, paste the result into the model you already use.

pip install llmscribe
Open on PyPIGitHub