Atlassian Confluence

Connect AI to Your Confluence Knowledge Base

Transform how you access and interact with your team's knowledge by connecting Claude, Cursor AI, and other AI assistants directly to your Confluence spaces, pages, and documentation. Get instant answers from your knowledge base, search across all your spaces, and streamline your documentation workflow.

What You Can Do

• Ask AI about your documentation: "What's our API authentication process?"
• Search across all spaces: "Find all pages about security best practices"
• Get instant answers: "Show me the latest release notes from the Product space"
• Access team knowledge: "What are our HR policies for remote work?"
• Review page comments: "Show me the discussion on the architecture document"
• Create and update content: "Create a new page in the DEV space"

Perfect For

• Developers who need quick access to technical documentation and API guides
• Product Managers searching for requirements, specs, and project updates
• HR Teams accessing policy documents and employee resources quickly
• Support Teams finding troubleshooting guides and knowledge base articles
• Anyone who wants to interact with Confluence using natural language

Quick Start

Get up and running in 2 minutes:

1. Get Your Confluence Credentials

Generate a Confluence API Token:

1. Go to Atlassian API Tokens
2. Click Create API token
3. Give it a name like "AI Assistant"
4. Copy the generated token immediately (you won't see it again!)

2. Try It Instantly

# Set your credentials
export ATLASSIAN_SITE_NAME="your-company"  # for your-company.atlassian.net
export ATLASSIAN_USER_EMAIL="[email protected]"
export ATLASSIAN_API_TOKEN="your_api_token"

# List your Confluence spaces (TOON format by default)
npx -y @aashari/mcp-server-atlassian-confluence get --path "/wiki/api/v2/spaces"

# Get details about a specific space with field filtering
npx -y @aashari/mcp-server-atlassian-confluence get \
  --path "/wiki/api/v2/spaces/123456" \
  --jq "{id: id, key: key, name: name, type: type}"

# Get a page with JMESPath filtering
npx -y @aashari/mcp-server-atlassian-confluence get \
  --path "/wiki/api/v2/pages/789" \
  --jq "{id: id, title: title, status: status}"

# Search for pages (using CQL)
npx -y @aashari/mcp-server-atlassian-confluence get \
  --path "/wiki/rest/api/search" \
  --query-params '{"cql": "type=page AND space=DEV"}'

Connect to AI Assistants

For Claude Desktop Users

Add this to your Claude configuration file (~/.claude/claude_desktop_config.json):

{
  "mcpServers": {
    "confluence": {
      "command": "npx",
      "args": ["-y", "@aashari/mcp-server-atlassian-confluence"],
      "env": {
        "ATLASSIAN_SITE_NAME": "your-company",
        "ATLASSIAN_USER_EMAIL": "[email protected]",
        "ATLASSIAN_API_TOKEN": "your_api_token"
      }
    }
  }
}

Restart Claude Desktop, and you'll see the confluence server in the status bar.

For Other AI Assistants

Most AI assistants support MCP (Cursor AI, Continue.dev, and others). Install the server globally:

npm install -g @aashari/mcp-server-atlassian-confluence

Then configure your AI assistant to use the MCP server with STDIO transport. The binary is available as mcp-atlassian-confluence after global installation.

Alternative: Configuration File

Create ~/.mcp/configs.json for system-wide configuration:

{
  "confluence": {
    "environments": {
      "ATLASSIAN_SITE_NAME": "your-company",
      "ATLASSIAN_USER_EMAIL": "[email protected]",
      "ATLASSIAN_API_TOKEN": "your_api_token"
    }
  }
}

Alternative config keys: The system also accepts "atlassian-confluence", "@aashari/mcp-server-atlassian-confluence", or "mcp-server-atlassian-confluence" instead of "confluence".

Using Environment Variables

You can also configure credentials using environment variables or a .env file:

# Create a .env file in your project directory
cat > .env << EOF
ATLASSIAN_SITE_NAME=your-company
[email protected]
ATLASSIAN_API_TOKEN=your_api_token
DEBUG=false
EOF

The server will automatically load these values from:

1. Environment variables
2. .env file in the current directory
3. ~/.mcp/configs.json (as shown above)

Available Tools

This MCP server provides 5 generic tools that can access any Confluence API endpoint:

Tool	Description
conf_get	GET any Confluence API endpoint (read data)
conf_post	POST to any endpoint (create resources)
conf_put	PUT to any endpoint (replace resources)
conf_patch	PATCH to any endpoint (partial updates)
conf_delete	DELETE from any endpoint (remove resources)

Tool Parameters

All tools share these common parameters:

• path (required): The API endpoint path (e.g., /wiki/api/v2/spaces)
• queryParams (optional): Query parameters as key-value pairs (e.g., {"limit": "25", "space-id": "123"})
• jq (optional): JMESPath expression to filter/transform the response (e.g., results[*].{id: id, title: title})
• outputFormat (optional): Output format - "toon" (default, 30-60% fewer tokens) or "json"

Tools that accept a request body (conf_post, conf_put, conf_patch):

• body (required): Request body as a JSON object

Common API Paths

Spaces:

• /wiki/api/v2/spaces - List all spaces
• /wiki/api/v2/spaces/{id} - Get space details

Pages:

• /wiki/api/v2/pages - List pages (use space-id query param to filter)
• /wiki/api/v2/pages/{id} - Get page details
• /wiki/api/v2/pages/{id}/body - Get page body (use body-format param)
• /wiki/api/v2/pages/{id}/children - Get child pages
• /wiki/api/v2/pages/{id}/labels - Get page labels

Comments:

• /wiki/api/v2/pages/{id}/footer-comments - List/add footer comments
• /wiki/api/v2/pages/{id}/inline-comments - List/add inline comments
• /wiki/api/v2/footer-comments/{comment-id} - Get/update/delete comment

Blog Posts:

• /wiki/api/v2/blogposts - List blog posts
• /wiki/api/v2/blogposts/{id} - Get blog post

Search:

• /wiki/rest/api/search - Search content (use cql query param)

TOON Output Format

What is TOON? TOON (Token-Oriented Object Notation) is a format optimized for LLM token efficiency, reducing token costs by 30-60% compared to JSON. It's the default output format for all tools.

Benefits:

• Tabular arrays use fewer tokens than JSON arrays
• Minimal syntax overhead (no quotes, brackets, commas where unnecessary)
• Still human-readable and parseable

When to use JSON instead:

• When you need standard JSON for other tools
• When debugging or manual inspection is needed

Example comparison:

// JSON format (verbose)
{"results": [{"id": "123", "title": "My Page"}, {"id": "456", "title": "Other Page"}]}

// TOON format (efficient)
results:
  - id: 123
    title: My Page
  - id: 456
    title: Other Page

To use JSON instead of TOON, set outputFormat: "json" in your request.

JMESPath Filtering

All tools support optional JMESPath (jq) filtering to extract specific data and reduce token costs:

# Get just space names and keys
npx -y @aashari/mcp-server-atlassian-confluence get \
  --path "/wiki/api/v2/spaces" \
  --jq "results[].{id: id, key: key, name: name}"

# Get page title and status
npx -y @aashari/mcp-server-atlassian-confluence get \
  --path "/wiki/api/v2/pages/123456" \
  --jq "{id: id, title: title, status: status}"

IMPORTANT: Always use the jq parameter to filter responses to only the fields you need. Unfiltered responses can be very large and expensive in token costs.

JMESPath Syntax Reference:

• Official docs: jmespath.org
• Common patterns:
  • results[*] - All items in results array
  • results[0] - First item only
  • results[*].id - Just IDs from all items
  • results[*].{id: id, title: title} - Create objects with selected fields
  • results[?status=='current'] - Filter by condition

Real-World Examples

Explore Your Knowledge Base

Ask your AI assistant:

• "List all the spaces in our Confluence"
• "Show me details about the Engineering space"
• "What pages are in our Product space?"
• "Find the latest pages in the Marketing space"

Search and Find Information

Ask your AI assistant:

• "Search for pages about API authentication"
• "Find all documentation with 'security' in the title"
• "Show me pages labeled with 'getting-started'"
• "Search for content in the DEV space about deployment"

Access Specific Content

Ask your AI assistant:

• "Get the content of the API Authentication Guide page"
• "Show me the onboarding checklist document"
• "What's in our security policies page?"
• "Display the latest release notes"

Create and Update Content

Ask your AI assistant:

• "Create a new page in the DEV space titled 'API Guide'"
• "Add a comment to the architecture document"
• "Update the page content with the new release info"

CLI Commands

The CLI mirrors the MCP tools for direct terminal access. All commands support the same parameters as the tools.

Available Commands

• get - GET any Confluence endpoint
• post - POST to any endpoint
• put - PUT to any endpoint
• patch - PATCH any endpoint
• delete - DELETE from any endpoint

CLI Parameters

All commands:

• -p, --path <path> (required) - API endpoint path
• -q, --query-params <json> (optional) - Query parameters as JSON
• --jq <expression> (optional) - JMESPath filter expression
• -o, --output-format <format> (optional) - Output format: toon (def

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README truncated. View full README on GitHub.