ai_writers_workshop

AI Writers Workshop provides a modular, project-based environment for narrative creation and analysis. It offers managers for projects, characters, plots, and scenes, plus a knowledge graph to capture relationships between entities, symbols, and themes. You can create writing projects, craft characters with archetypes, generate scenes and outlines, and then compile narratives into markdown or other formats. The built-in tools expose operations like listing plots, creating custom plotlines, integrating patterns, and exploring narrative graphs, enabling a cohesive creative workflow across multiple projects. Use the project scope to organize character development, plot progression, and symbolic connections, and leverage the knowledge graph to surface relationships and thematic threads across your storytelling elements.

Prerequisites:

• Python 3.8+ installed on your system
• Access to the internet to install Python packages

Step-by-step installation:

1. (Optional) Create a virtual environment python -m venv aw_env source aw_env/bin/activate # On Windows use aw_env\Scripts\activate

2. Install the AI Writers Workshop package (replace with the actual package name if different) pip install ai-writers-workshop

3. Verify installation by running a quick help check or version check python -m ai_writers_workshop --help # or a provided CLI entry if available

4. Start the MCP server python -m ai_writers_workshop

5. If you run behind a firewall or require specific ports, set environment variables accordingly (see mcp_config.env values in this document).

Tips and common considerations:

• Use a dedicated data path to keep projects and knowledge graph data organized and portable (AWW_DATA_PATH).
• If you enable verbose logging (AWW_LOG_LEVEL=DEBUG), monitor performance and identify long-running pattern analyses.
• The knowledge graph stores entities and relations under knowledge_graph/; back up this directory regularly for safety.
• For collaboration, leverage project-based scoping so team members work on distinct projects without interfering with others.
• If you encounter module import errors, ensure the Python environment is activated and the package version is compatible with your Python interpreter.