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Confluence Knowledge Base MCP Server

by marcciosilva
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Confluence Knowledge Base MCP Server

An MCP server that turns your Confluence documentation into an AI-powered knowledge base for Gemini CLI. Ask natural language questions about your systems and get answers from your actual documentation.

Quick Start

One-Command Setup

git clone <this-repo> cd confluence-knowledge-base ./install.sh

The interactive wizard will:

  1. ✅ Install dependencies in a virtual environment

  2. ✅ Ask for your Confluence credentials

  3. ✅ Discover your spaces

  4. ✅ Help you choose which spaces to index

  5. ✅ Build the initial knowledge base

  6. ✅ Configure Gemini CLI automatically (merges with existing config)

What You'll Need

Before running the installer:

  1. Confluence API Token

  2. Your Confluence URL

    • Example: https://yourcompany.atlassian.net

  3. Python 3.8+ installed

    • The installer creates a virtual environment automatically (no system-wide packages needed)

  4. Gemini CLI installed

Usage

Once installed, just start Gemini CLI and ask questions:

gemini
> How does our authentication system work? > What's the process for deploying to production? > Explain our database migration strategy > What are the API rate limits?

Gemini will automatically retrieve relevant documentation and answer your questions!

How It Works

1. Your Confluence docs → Downloaded and indexed (one-time) 2. You ask a question → Semantic search finds relevant chunks 3. Gemini gets context → Answers based on YOUR docs

Technologies Used

  • FastMCP - MCP server framework

  • ChromaDB - Local vector database

  • sentence-transformers - Semantic search

  • Confluence REST API - Documentation retrieval

Project Structure

confluence-knowledge-base/ ├── install.sh # Interactive setup wizard ├── confluence_knowledge_base.py # Main MCP server ├── confluence_kb_with_staleness.py # Version with auto-reindex ├── find_space_keys.py # Space discovery utility ├── requirements.txt # Python dependencies ├── KNOWLEDGE_BASE_SETUP.md # Detailed setup guide └── README.md # This file

Configuration

After installation, configuration is stored in:

  • Credentials: ~/.confluence_mcp.env

  • Index: ~/.confluence_mcp/index/

  • Gemini Config: ~/.gemini/settings.json

  • Virtual Environment: ./venv/ (in the project directory)

Updating Documentation

When your Confluence docs are updated:

Option 1: Ask Gemini

> Reindex the Confluence documentation

Option 2: Command line

./venv/bin/python confluence_knowledge_base.py

Option 3: Automated (Weekly)

Set up a cron job (see REINDEXING_GUIDE.md)

Customization

Change indexed spaces

Edit ~/.confluence_mcp.env:

export CONFLUENCE_SPACES="ENG,DEVOPS,TEAM"

Then rebuild the index.

Adjust chunk size

In confluence_knowledge_base.py:

CHUNK_SIZE = 1000 # Default: 1000 characters CHUNK_OVERLAP = 200 # Default: 200 characters

Change embedding model

For better quality (slower, larger):

self.embedding_model = SentenceTransformer('all-mpnet-base-v2')

Troubleshooting

"Connection failed"

Check that:

  • Your Confluence URL is correct

  • Your API token is valid

  • You have internet connectivity

"No spaces found"

You might not have access to any Confluence spaces. Ask your admin for access.

Slow indexing

Normal for large documentation sets (500+ pages). Reduce spaces or run overnight.

Wrong/outdated answers

Your index is cached! Reindex when docs are updated:

rm -rf ~/.confluence_mcp ./install.sh

Advanced Usage

Manual space discovery

source ~/.confluence_mcp.env python3 find_space_keys.py

Staleness detection

Use the enhanced version with automatic staleness warnings:

# In ~/.gemini/settings.json, change the args to: "args": ["confluence_kb_with_staleness.py"]

Add environment variables:

export MAX_INDEX_AGE_DAYS=7 export AUTO_REINDEX=true

Scheduled reindexing

See REINDEXING_GUIDE.md for cron job setup.

FAQ

Q: Does this modify my Confluence documentation? A: No, it's read-only. It only downloads and indexes content.

Q: Where is my data stored? A: Locally in ~/.confluence_mcp/index/. Nothing is sent to external services except Gemini API calls.

Q: How much does it cost? A: The MCP server is free. You only pay for Gemini API usage (queries to the AI).

Q: Can I use this with Claude instead of Gemini? A: Yes! MCP is a standard protocol. Just configure Claude Desktop to use this MCP server.

Q: How often should I reindex? A: Depends on how often your docs are updated. Weekly is common. Daily if very active.

Q: Can I exclude certain pages? A: Not by default, but you can modify confluence_knowledge_base.py to filter by title, label, etc.

Q: What about attachments/PDFs? A: Currently only page content is indexed. Attachments could be added with additional code.

Documentation

  • KNOWLEDGE_BASE_SETUP.md - Comprehensive setup guide

  • REINDEXING_GUIDE.md - Strategies for keeping docs fresh

Contributing

Feel free to:

  • Add features (write capabilities, attachment support, etc.)

  • Improve chunking strategies

  • Add better error handling

  • Create additional tools

License

[Your license here]

Support

For issues or questions:

  1. Check the troubleshooting section above

  2. Review the detailed guides in /docs

  3. Open an issue on GitHub

Ready to get started? Just run:

./install.sh

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

How are these scores calculated?

local-only server

The server can only run on the client's local machine because it depends on local resources.

Turns Confluence documentation into an AI-powered knowledge base, enabling natural language questions about your systems with answers retrieved from your actual documentation through semantic search.

  1. Quick Start
    1. One-Command Setup
    2. What You'll Need
  2. Usage
    1. How It Works
      1. Technologies Used
    2. Project Structure
      1. Configuration
        1. Updating Documentation
      2. Customization
        1. Change indexed spaces
        2. Adjust chunk size
        3. Change embedding model
      3. Troubleshooting
        1. "Connection failed"
        2. "No spaces found"
        3. Slow indexing
        4. Wrong/outdated answers
      4. Advanced Usage
        1. Manual space discovery
        2. Staleness detection
        3. Scheduled reindexing
      5. FAQ
        1. Documentation
          1. Contributing
            1. License
              1. Support

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