Stop pasting files. Get real architecture-aware answers.
Generate complete project context in seconds.
Turn any Java, Kotlin, or Python project into a single AI-ready context.txt (or context.md) in seconds.
Jctx "C:\projects\MyApp"
→ context.txt written (Java: 39 files | Kotlin: 12 files | Python: 15 files | POM: 1 file | Gradle: 1 file)
No config. No dependencies. Just Python and a folder.
You're working on a Java, Kotlin, or Python project. You open an AI chat to get help. Before you can even ask your question, you spend 10 minutes copy-pasting files, explaining your class structure, summarising what each module does.
Before: ChatGPT suggests random classes
After: ChatGPT tells exactly which class to modify and why
Jctx does all of that in one command.
It scans your project and writes a clean, structured context.txt (or context.md) — every class, every field, every method signature, every Javadoc/KDoc comment, and your build files — formatted so an AI can immediately understand your entire codebase.
It also provides Token Count Estimation, Language Percentages, and a Dependency Graph — all printed to your console automatically.
Paste it. Ask your question. Get useful answers.
Click to expand sample context.txt (Plain Text - Default)
================================================================
JCTX v2.0.0 - Java, Kotlin & Python Context Extractor
Project : C:\projects\Talken
Date : 2026-03-31 12:00:00
Files : Java: 39 file(s) | Kotlin: 5 file(s) | Python: 2 file(s) | POM: 1 file(s) | Gradle: 1 file(s)
================================================================
================================================================
SECTION 1 - PROJECT FILE TREE
================================================================
Talken\
├── src\
│ └── main\
│ ├── java\
│ │ └── org\
│ │ └── flexstudios\
│ │ └── talken\
│ │ ├── Controls.java
│ │ └── TalkenClient.java
│ └── kotlin\
│ └── org\
│ └── flexstudios\
│ └── talken\
│ └── UserProfile.kt
├── build.gradle
└── pom.xml
================================================================
SECTION 2 - POM.XML CONTENT
================================================================
----------------------------------------------------------------
FILE: pom.xml
----------------------------------------------------------------
<?xml version="1.0" encoding="UTF-8"?>
<project>
<modelVersion>4.0.0</modelVersion>
<groupId>org.flexstudios</groupId>
<artifactId>talken</artifactId>
<version>1.0.0</version>
</project>
================================================================
SECTION 3 - KOTLIN CLASS AND MEMBER DETAILS
================================================================
----------------------------------------------------------------
FILE: src\main\kotlin\org\flexstudios\talken\UserProfile.kt
----------------------------------------------------------------
CLASS: UserProfile
DOC : Represents the user's local profile settings.
DATA MEMBERS:
· private val String displayName
· private val String email
METHODS:
[1] String getAboutSection()
DOC: (no documentation)
================================================================
END OF REPORT
================================================================
Option 1: PyPI (Recommended) The easiest way to install Jctx on any OS (Windows, macOS, Linux) is via pip:
pip install jctxThe jctx command will be instantly available in your terminal.
Option 2: Manual Download (Windows)
- Download The Latest Release Zip.
- Unzip it
- Right-click
Setup.bat→ Run as administrator - Open a new terminal
jctx "C:\path\to\your\java\project"No admin rights? Copy
jctx.py+jctx.batanywhere and runjctx.batdirectly.
Not on Windows? Run
python jctx.py "path/to/project"on any OS with Python 3.8+.
Jctx <project_folder> [--md] [--slim] [--no-tree] [--clipboard] [--print] [--version] [--help]
| Flag | Effect |
|---|---|
| (none) | Saves context.txt into your project folder and prints token estimates |
--md |
Outputs a cleanly formatted Markdown file (context.md) instead of plain text |
--slim |
Slim mode: output only class names and method signatures (omits fields and docs) to save tokens |
--no-tree |
Skips the file tree section (shorter output) |
--clipboard |
Copies the generated report directly to your clipboard |
--print |
Also prints to the console |
--version |
Shows the Jctx version |
--help |
Shows help |
Paste context.txt (or the contents of context.md) into any AI chat and ask your question:
"Here's my Java/Kotlin/Python project structure: [paste]. I want to refactor the messaging module to use WebSockets — where should I start?"
Works great with Claude, ChatGPT, Gemini, and any other AI that accepts long text input.
After generating the file, Jctx prints a full analytics dashboard to your console:
Shows the exact split of Java vs Kotlin code with a visual progress bar:
================================================================
LANGUAGE PERCENTAGES
================================================================
Java : 60.2% ██████████████████████████████░░░░░░░░░░░░░░░░░░░░ (~23,400 tokens)
Kotlin : 28.1% ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ (~10,910 tokens)
Python : 11.7% █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ (~ 4,560 tokens)
================================================================
Automatically maps which of your project classes depend on which (only project-internal references — no external library noise):
================================================================
DEPENDENCY GRAPH (project-internal)
================================================================
EncryptionModule → (none)
MessagingModule → EncryptionModule, UserProfile
TalkenClient → EncryptionModule, MessagingModule, UserProfile
UserProfile → (none)
================================================================
Shows the total token count with a breakdown by section and checks whether your context fits each major AI model's context window:
================================================================
TOKEN ESTIMATE
================================================================
Total tokens : ~34,767
Language Breakdown:
Java : ~ 23,400 ( 59.5%)
Kotlin : ~ 10,910 ( 27.7%)
Python : ~ 4,560 ( 11.6%)
Build files : ~ 145 ( 0.4%)
File tree : ~ 312 ( 0.8%)
Context Window Fit:
Y Llama 4 Scout (10M) Y Gemini 3.1 (2M) Y Grok (2M)
Y GPT-5.4 (1M) Y Claude 4.6 (1M) Y Qwen 3 (1M)
================================================================
Place a .jctxignore file in the project root to exclude additional directories or files from context extraction:
# Skip test directories
**/test/**
# Skip generated code
generated/
# Skip specific file patterns
*.test.java| Pattern | Meaning |
|---|---|
dirname/ |
Skip any directory named dirname |
**/test/** |
Skip any directory named test anywhere in the tree |
*.test.java |
Skip files matching the glob pattern |
# comment |
Lines starting with # are ignored |
When a .jctxignore is detected, the console banner shows:
.jctxignore: yes (2 dirs, 1 patterns)
| What | Detail |
|---|---|
| File tree | Full project structure, build folders excluded |
| Build Files | Full content of your pom.xml, build.gradle, requirements.txt, and pyproject.toml |
| Classes | Java/Kotlin classes and interfaces, Python classes, plus all docstrings/JavaDocs/KDocs |
| Fields | Type, name, access modifier, val/var (Kotlin), instance vars (self.x), inline comments |
| Methods | Numbered list — return type, name, params, decorators, top-level Python/Kotlin functions |
Auto-ignored: build/, target/, .idea/, .git/, node_modules/, .gradle/, .class, .jar, and all other build artifacts. Customize further with .jctxignore.
- Python 3.8 or newer — python.org
- Works on Windows, macOS, Linux
- Kotlin support
- Markdown output mode (
context.md) - Multi-language project estimations (mixed Java + Kotlin percentages)
- Token count estimate alongside output
- Clipboard support and Slim mode
- Dependency graph (project-internal)
-
.jctxignorecustom exclusions - Cross-platform packaging (PyPI / pip)
- Python language support
- Architecture diagram generation (
--diagram)
MIT — free to use, modify, and share.