Connects to Atlassian Confluence API to provide custom MCP functionality for interacting with Confluence content and spaces
Integrates with Ollama to leverage local language models (like tinyllama) for processing and generating content
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Confluence MCP Server search for documentation about API authentication"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A server application for integrating with Atlassian Confluence using Python.
Connects to Atlassian Confluence API
Custom endpoints for MCP functionality
Related MCP server: MCP Atlassian
Clone the repository:
git clone https://github.com/LakshmiGayathri19/MCP.git
cd MCPInstall dependencies:
pip install -r requirements.txtConfigure your environment variables (do not hardcode secrets in your code):
ATLASSIAN_API_TOKEN=your_token_hereInstall Ollama (if not done)
Download Ollama and install it.
Pull a model (e.g., tinyllama)
ollama pull tinyllama
Run the server in one terminal tab:
python server.pyRun the client in another terminal tab:
python client.pyDo not commit secrets or API tokens to the repository.
If you accidentally commit a secret, remove it from your code and git history.
See GitHub’s guide for help.
MIT
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