Confluence MCP Server
MCP server for Confluence Cloud that enables searching, reading, managing documentation and linting for best practices.
README
Confluence MCP Server
Model Context Protocol (MCP) server for Confluence Cloud search and management. Enables Claude Code to connect to your Confluence instance for searching, reading, and managing documentation with built-in best-practice linting.
Features
Phase 1: Connection Proof ✅
confluence_ping- Test connection and verify authenticationconfluence_whoami- Get authenticated user informationconfluence_list_spaces- List accessible Confluence spaces
Phase 2: Read & Search ✅
confluence_search- Search using CQL (Confluence Query Language)confluence_get_page_by_title- Find pages by exact titleconfluence_list_pages- List pages in a spaceconfluence_get_page- Get full page content and metadataconfluence_get_page_metadata- Get metadata without bodyconfluence_get_children- Get child pages
Phase 3: Safe Write Operations ✅
confluence_create_page- Create new pages (with dry-run)confluence_update_page- Update existing pages (with dry-run)confluence_add_labels- Add labels to pagesconfluence_remove_labels- Remove labels from pagesconfluence_archive_page- Archive pages (with dry-run)
All write operations support dryRun: true for previewing changes.
Phase 4: Best Practices ✅
confluence_lint_page- Check pages for best practice violationsconfluence_suggest_improvements- Get actionable improvement suggestions
Checks for:
- Title conventions (length, formatting, generic terms)
- Missing metadata (owner, last reviewed date)
- Content structure (headings, paragraphs, code blocks)
- Labels (missing or non-standard)
- Staleness (pages not updated in 6+ months)
- Excessive nesting depth (4+ levels)
Setup
1. Install Dependencies
cd ~/repos/confluence-mcp-server
npm install
2. Configure Environment
Create a .env file from the template:
cp .env.example .env
Edit .env with your Confluence details:
# Your Confluence Cloud instance
CONFLUENCE_BASE_URL=https://your-domain.atlassian.net
# Your Atlassian account email
CONFLUENCE_EMAIL=your-email@example.com
# API token (generate at https://id.atlassian.com/manage-profile/security/api-tokens)
CONFLUENCE_API_TOKEN=your-api-token-here
# Enable write operations (default: false)
CONFLUENCE_WRITE_ENABLED=false
# Optional: Restrict write operations to specific spaces
# CONFLUENCE_ALLOWED_SPACES=TEAM,DOCS,WIKI
# Optional: Enable audit logging (default: true)
CONFLUENCE_AUDIT_LOG=true
3. Generate Confluence API Token
- Go to https://id.atlassian.com/manage-profile/security/api-tokens
- Click "Create API token"
- Give it a name (e.g., "Claude Code MCP")
- Copy the token and paste it into your
.envfile
4. Add to Claude Code Configuration
Edit ~/.claude.json and add to the global mcpServers section:
{
"mcpServers": {
"confluence": {
"type": "stdio",
"command": "/Users/joshuamullet/repos/confluence-mcp-server/start-mcp-server.sh",
"args": [],
"env": {}
}
}
}
Important:
- Use the ABSOLUTE path to
start-mcp-server.sh - Add to global
mcpServers, NOT inside a project'smcpServers - Must include
"type": "stdio"field
5. Restart Claude Code
Fully restart Claude Code to load the new MCP server:
# Exit current session
/exit
# Start new session
claude-code
6. Verify Connection
In Claude Code, check that the server is loaded:
/mcp
You should see confluence listed with connection status.
Usage
Connection Test
Test your Confluence connection:
Can you ping the Confluence server and show me the current user?
Claude will call confluence_ping and confluence_whoami to verify connectivity.
Search Examples
Search all spaces:
Search Confluence for pages about "API documentation"
Search specific space:
Search for pages in the TEAM space that contain "deployment"
Advanced CQL:
Search Confluence using this CQL: type=page AND space=DOCS AND lastModified >= "2025-01-01"
Read Examples
Get page by title:
Get the page titled "Getting Started" from the TEAM space
Get page by ID:
Show me the content of Confluence page 123456
List pages:
List all pages in the DOCS space
Get page tree:
Show me all child pages of page 123456
Best Practices Linting
Lint a page:
Lint Confluence page 123456 for best practice issues
Get improvement suggestions:
Suggest improvements for Confluence page 123456
Example output:
{
"pageId": "123456",
"pageTitle": "API Documentation",
"totalFindings": 3,
"findings": [
{
"severity": "warning",
"category": "metadata",
"message": "Missing owner or contact information",
"recommendation": "Add an 'Owner' or 'Contact' section"
},
{
"severity": "info",
"category": "labels",
"message": "Page has no labels",
"recommendation": "Add labels to improve discoverability"
}
]
}
Write Operations (when enabled)
Important: Write operations require CONFLUENCE_WRITE_ENABLED=true in your .env file.
Create a page:
Create a new page in the TEAM space titled "New Feature" with this content:
<h1>Overview</h1>
<p>This is a new feature.</p>
Update a page (dry-run first):
Update page 123456 with a new title "Updated Title" - show me what will change first
Add labels:
Add labels "documentation" and "api" to page 123456
Security
Authentication
- Uses Confluence Cloud API tokens (not passwords)
- API tokens are stored in
.env(gitignored, never committed) - Authentication via HTTP Basic Auth (email + API token)
Write Protection
- Write operations disabled by default
- Requires explicit
CONFLUENCE_WRITE_ENABLED=true - All write operations support dry-run mode
- Optional space allowlist restricts modifications
Audit Logging
- All tool calls are logged to stderr
- Logs include: timestamp, tool name, parameters, success/error
- Sensitive data (API tokens) never logged
- View logs:
tail -f ~/.claude/logs/*.log
Rate Limiting
- Automatically detects 429 responses
- Returns clear error with retry-after information
- Implements basic retry logic with backoff
Troubleshooting
Server not appearing in /mcp
-
Check
~/.claude.jsonconfiguration:- Is the server in the global
mcpServerssection? - Is the path to
start-mcp-server.shabsolute and correct? - Is
"type": "stdio"present?
- Is the server in the global
-
Check server starts manually:
cd ~/repos/confluence-mcp-server node mcp-server.jsShould output:
Confluence MCP Server running on stdio -
Check Claude Code logs:
tail -f ~/.claude/logs/*.log
Authentication errors
- Verify
CONFLUENCE_BASE_URLis correct (should behttps://your-domain.atlassian.net) - Verify
CONFLUENCE_EMAILmatches your Atlassian account - Regenerate API token if needed
- Test credentials manually:
curl -u "your-email:your-token" "https://your-domain.atlassian.net/wiki/rest/api/space"
Write operations disabled
- Check
CONFLUENCE_WRITE_ENABLED=truein.env - Restart Claude Code after changing
.env - Verify the setting loaded: server logs show "Write operations: ENABLED"
Missing environment variables
Error: Missing required environment variables
Solution:
- Ensure
.envfile exists in the server directory - Verify all required variables are set
- Check dotenv is loading (see server startup logs)
API Reference
Search with CQL
CQL (Confluence Query Language) examples:
type=page AND space=TEAM
type=page AND title~"API"
type=page AND space=DOCS AND lastModified >= "2025-01-01"
type=page AND label="documentation"
creator=currentUser()
See Confluence CQL documentation for more.
Pagination
Most list operations support pagination:
{
"limit": 25, // Results per page (max 100)
"start": 0 // Offset (0 = first page, 25 = second page, etc.)
}
Dry Run Mode
All write operations support dry-run:
{
"pageId": "123456",
"title": "New Title",
"dryRun": true // Preview changes without applying
}
Returns what would be changed without making actual modifications.
Development
Project Structure
confluence-mcp-server/
├── mcp-server.js # Main MCP server (loads dotenv first)
├── start-mcp-server.sh # Shell wrapper for Claude Code
├── tools/
│ ├── confluence-client.js # Confluence REST API client
│ └── best-practices.js # Linting and suggestions
├── package.json
├── .env # Your credentials (gitignored)
├── .env.example # Template
├── .gitignore
└── README.md
Testing Manually
Test individual API calls:
cd ~/repos/confluence-mcp-server
node -e "
import('./tools/confluence-client.js').then(async ({ ConfluenceClient }) => {
const client = new ConfluenceClient(
process.env.CONFLUENCE_BASE_URL,
process.env.CONFLUENCE_EMAIL,
process.env.CONFLUENCE_API_TOKEN
);
const result = await client.ping();
console.log(result);
});
"
Resources
- Confluence Cloud REST API
- Advanced searching using CQL
- Model Context Protocol
- Confluence API Authentication
License
ISC
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.