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Common_Chronicle

Common Chronicle turns messy context into structured, sourced timelines.

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add --transport stdio intelligent-internet-common_chronicle python -m common_chronicle \
  --env GOOGLE_API_KEY="your-google-api-key (optional)" \
  --env OPENAI_API_KEY="your-openai-api-key" \
  --env SOURCE_LANGUAGES="comma-separated list of languages to search (optional)"

How to use

Common Chronicle is an AI-assisted timeline builder that aggregates events from diverse sources, normalizes dates, and links each item back to its original source. It focuses on an opinion-driven workflow: you start with a question or hypothesis, the AI retrieves and ranks relevant events, and it automatically assembles a structured, research-ready timeline with citations. Use the built timeline to explore historical narratives, compare perspectives across sources, and extract evidence for arguments or storytelling. The system supports multi-language data gathering, relevance-focused filtering, and export options so you can share or further analyze results.

How to install

Prerequisites:

  • Python 3.12 or newer
  • Git
  • Optional: a virtual environment tool (venv, conda, etc.)
  1. Clone the repository:
git clone https://github.com/Intelligent-Internet/Common_Chronicle.git
cd Common_Chronicle
  1. Create and activate a virtual environment:
python -m venv venv
# On Windows
venv\Scripts\activate
# On macOS/Linux
source venv/bin/activate
  1. Install Python dependencies:
pip install -r requirements.txt
  1. Install or prepare any optional AI-provider tools you plan to use (OpenAI, Google Gemini, etc.). Set environment variables as described in the mcp_config section.

  2. Run the MCP server:

python -m common_chronicle

If you prefer a Docker setup, see the environment notes and adapt accordingly to run the image with your API keys and configuration.

Additional notes

Environment variables:

  • OPENAI_API_KEY: required if using OpenAI-compatible providers
  • GOOGLE_API_KEY: optional for Google Gemini integration
  • SOURCE_LANGUAGES: comma-separated list to broaden source coverage Configuration tips:
  • Ensure your API keys are kept secure and not committed to version control
  • If using multiple providers, confirm rate limits and cost settings align with your usage
  • For large datasets, consider enabling incremental indexing and chunked exports to manage memory usage Common issues:
  • Import or module not found errors: ensure you activated the virtual environment and installed dependencies
  • API key authentication failures: verify keys are valid and have necessary permissions
  • Date normalization inconsistencies: adjust locale or date parsing rules via config if available

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