Which integrations are available for this server?

Used for text chunking in the smart features implementation to process and embed wiki documents for semantic search and retrieval. Used for AI-powered smart features including text embeddings (text-embedding-3-small) for vector search and GPT-4o-mini for RAG-based Q&A, document summarization, tag suggestions, and diagram generation. Enables LLMs to interact with [Outline](/mcp/servers/integrations/outline) wiki through structured API calls, providing document management, search, collections, comments, and AI-powered features including RAG-based Q&A, summarization, and semantic document discovery.

Outline Wiki MCP Server

npm version License: MIT

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A Model Context Protocol (MCP) server that enables LLMs to interact with Outline wiki through structured API calls. This server provides document management, search, collections, comments, and AI-powered smart features including RAG-based Q&A.

Supported Clients

Client	Tools	Resources	Prompts
Claude Desktop	✅	✅	✅
Claude Code	✅	✅	✅
VS Code GitHub Copilot	✅	✅	✅
Cursor	✅	-	✅
Windsurf	✅	-	-
ChatGPT Desktop	✅	-	-

Getting Started

Requirements

Node.js 18.0.0 or higher
Outline instance with API access
(Optional) OpenAI API key for smart features

Getting Your Outline API Token

Log in to your Outline instance
Go to Settings → API
Click Create API Key
Copy the generated token (starts with ol_api_)

Installation

Add to your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{ "mcpServers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx" } } } }

Run the following command:

claude mcp add outline -e OUTLINE_URL=https://your-outline-instance.com -e OUTLINE_API_TOKEN=ol_api_xxxxxxxxxxxxx -- npx -y outline-mcp-server

Or add to ~/.claude.json (global) or .mcp.json (project-local):

{ "mcpServers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx" } } } }

Note: The ~/.claude/settings.json file is ignored for MCP servers. Use ~/.claude.json or .mcp.json instead.

Add to your VS Code settings (.vscode/mcp.json):

{ "servers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx" } } } }

Add to Cursor MCP settings (~/.cursor/mcp.json):

{ "mcpServers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx" } } } }

Add to Windsurf MCP settings (~/.codeium/windsurf/mcp_config.json):

{ "mcpServers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx" } } } }

ChatGPT supports MCP through its desktop app. Add the server in Settings → MCP Servers with:

Command: npx
Arguments: -y outline-mcp-server
Environment variables as shown above

Configuration

Environment Variables

Variable	Description	Required	Default
`OUTLINE_URL`	Your Outline instance URL	Yes	`https://app.getoutline.com`
`OUTLINE_API_TOKEN`	Your Outline API token	Yes	-
`READ_ONLY`	Enable read-only mode	No	`false`
`DISABLE_DELETE`	Disable delete operations	No	`false`
`MAX_RETRIES`	API retry attempts	No	`3`
`RETRY_DELAY_MS`	Retry delay (ms)	No	`1000`
`ENABLE_SMART_FEATURES`	Enable AI features	No	`false`
`OPENAI_API_KEY`	OpenAI API key	No*	-

* Required when ENABLE_SMART_FEATURES=true

Smart Features Configuration

To enable AI-powered features (RAG Q&A, summarization, etc.), add these to your config:

{ "mcpServers": { "outline": { "command": "npx", "args": ["-y", "outline-mcp-server"], "env": { "OUTLINE_URL": "https://your-outline-instance.com", "OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx", "ENABLE_SMART_FEATURES": "true", "OPENAI_API_KEY": "sk-xxxxxxxxxxxxx" } } } }

Tools

Search & Discovery

Tool	Description
`search_documents`	Search documents by keyword with pagination
`get_document_id_from_title`	Find document ID by title
`list_collections`	Get all collections
`get_collection_structure`	Get document hierarchy in a collection
`list_recent_documents`	Get recently modified documents

Document Operations

Tool	Description
`get_document`	Get full document content by ID
`export_document`	Export document in Markdown
`create_document`	Create a new document
`update_document`	Update document (supports append)
`move_document`	Move document to another location

Document Lifecycle

Tool	Description
`archive_document`	Archive a document
`unarchive_document`	Restore archived document
`delete_document`	Delete document (soft/permanent)
`restore_document`	Restore from trash
`list_archived_documents`	List archived documents
`list_trash`	List trashed documents

Comments & Collaboration

Tool	Description
`add_comment`	Add comment (supports replies)
`list_document_comments`	Get document comments
`get_comment`	Get specific comment
`get_document_backlinks`	Find linking documents

Collection Management

Tool	Description
`create_collection`	Create collection
`update_collection`	Update collection
`delete_collection`	Delete collection
`export_collection`	Export collection
`export_all_collections`	Export all collections

Batch Operations

Tool	Description
`batch_create_documents`	Create multiple documents
`batch_update_documents`	Update multiple documents
`batch_move_documents`	Move multiple documents
`batch_archive_documents`	Archive multiple documents
`batch_delete_documents`	Delete multiple documents

Smart Features (AI-Powered)

Requires ENABLE_SMART_FEATURES=true and OPENAI_API_KEY.

Tool	Description
`smart_status`	Check status and indexed count
`sync_knowledge`	Sync docs to vector database
`ask_wiki`	RAG-based Q&A on wiki content
`summarize_document`	Generate AI summary
`suggest_tags`	AI-suggested tags
`find_related`	Find semantically related docs
`generate_diagram`	Generate Mermaid diagrams

Smart Features Usage

# 1. First, sync your wiki documents sync_knowledge # 2. Ask questions about your wiki ask_wiki: "What is our deployment process?" # 3. Summarize long documents summarize_document: { documentId: "doc-id", language: "Korean" } # 4. Find related content find_related: { documentId: "doc-id", limit: 5 }

Technology Stack

Component	Technology
Vector Database	LanceDB (embedded)
Embeddings	OpenAI text-embedding-3-small
LLM	GPT-4o-mini
Text Chunking	LangChain

Safety Features

Read-Only Mode

READ_ONLY=true

Restricts to read operations only: search, get, export, list operations, and all smart features.

Disable Delete

DISABLE_DELETE=true

Blocks: delete_document, delete_collection, batch_delete_documents

Development

# Clone repository git clone https://github.com/huiseo/outline-wiki-mcp.git cd outline-wiki-mcp # Install dependencies npm install # Build npm run build # Run tests npm test # Type check npm run typecheck

License

MIT License - see LICENSE for details.

Outline Wiki MCP Server

Outline Wiki MCP Server

Supported Clients

Getting Started

Requirements

Getting Your Outline API Token

Installation

Configuration

Environment Variables

Smart Features Configuration

Tools

Search & Discovery

Document Operations

Document Lifecycle

Comments & Collaboration

Collection Management

Batch Operations

Smart Features (AI-Powered)

Smart Features Usage

Technology Stack

Safety Features

Read-Only Mode

Disable Delete

Development

License

Links

Resources

Tools

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