QualCoder v2
A desktop qualitative data analysis (QDA) tool that helps researchers apply semantic codes to text, audio, video, images, and PDFs — with built-in AI assistance.
Choose Your Path
|
Path |
Description |
| Researcher |
User Guide |
Learn how to use QualCoder for your research projects |
| Developer |
Developer Guide |
Understand the architecture and contribute code |
| AI Agent |
MCP API Reference |
Connect via MCP to automate coding tasks |
| Designer |
Design System |
Browse 180+ reusable PySide6 components |
What Can QualCoder Do?
| Feature |
Description |
| Manage Sources |
Import text, PDF, image, audio, and video files |
| Apply Codes |
Create codes and apply them to text selections, image regions, or time ranges |
| Organize Cases |
Group sources by participant, site, or any category |
| AI Assistance |
Get code suggestions, detect duplicates, and auto-code with AI |
| Import & Export |
REFI-QDA, RQDA, codebooks, HTML, and CSV formats |
| MCP Integration |
AI agents can read, code, and analyze your data via the MCP protocol |
Quick Start
How It Works
graph LR
R([Researcher]) -->|UI| App
A([AI Agent]) -->|MCP| App
App --> Sources[Manage Sources]
App --> Codes[Apply Codes]
App --> Cases[Organize Cases]
App --> Exchange[Import & Export]
Sources --> DB[(Project Database)]
Codes --> DB
Cases --> DB
Both researchers and AI agents work with the same data through different interfaces — every change by either actor is immediately visible to the other.
Technology
|
|
| Desktop UI |
PySide6 (Qt 6) |
| Database |
SQLite (local-first) |
| AI Providers |
OpenAI, Anthropic, Ollama |
| Agent Protocol |
MCP (Model Context Protocol) |