Outline Wiki MCP Server
Enables LLMs to interact with Outline wiki for document management, search, and collections, with optional AI-powered features including RAG-based Q\&A, semantic search, and document summarization.
README
Outline Wiki MCP Server
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.
Why This Server?
Most Outline MCP servers provide basic API wrappers. This one adds optional Smart Features:
| Feature | What it does |
|---|---|
ask_wiki |
Ask questions in natural language, get answers based on your wiki content (RAG) |
find_related |
Find semantically similar documents, not just keyword matches |
summarize_document |
Generate summaries of long documents |
suggest_tags |
Get tag suggestions based on content analysis |
When you might need this:
- Your team's wiki has grown large and search isn't enough
- You want to query your documentation conversationally
- You need semantic search across your knowledge base
When basic MCP is sufficient:
- You only need CRUD operations on documents
- You don't want to set up OpenAI API
- Your wiki is small and well-organized
Smart features require ENABLE_SMART_FEATURES=true and an OpenAI API key. Without these, the server works as a standard Outline MCP.
Example Usage
User: "What's our policy on remote work?"
→ ask_wiki searches your wiki and returns an answer with source links
User: "Find documents related to the onboarding guide"
→ find_related returns semantically similar docs (not just keyword matches)
User: "Summarize the Q4 planning document"
→ summarize_document generates a concise summary in your preferred language
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
<details> <summary>Claude Desktop</summary>
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-smart-mcp"],
"env": {
"OUTLINE_URL": "https://your-outline-instance.com",
"OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx"
}
}
}
}
</details>
<details> <summary>Claude Code</summary>
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-smart-mcp
Or add to ~/.claude.json (global) or .mcp.json (project-local):
{
"mcpServers": {
"outline": {
"command": "npx",
"args": ["-y", "outline-smart-mcp"],
"env": {
"OUTLINE_URL": "https://your-outline-instance.com",
"OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx"
}
}
}
}
Note: The
~/.claude/settings.jsonfile is ignored for MCP servers. Use~/.claude.jsonor.mcp.jsoninstead.
</details>
<details> <summary>VS Code GitHub Copilot</summary>
Add to your VS Code settings (.vscode/mcp.json):
{
"servers": {
"outline": {
"command": "npx",
"args": ["-y", "outline-smart-mcp"],
"env": {
"OUTLINE_URL": "https://your-outline-instance.com",
"OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx"
}
}
}
}
</details>
<details> <summary>Cursor</summary>
Add to Cursor MCP settings (~/.cursor/mcp.json):
{
"mcpServers": {
"outline": {
"command": "npx",
"args": ["-y", "outline-smart-mcp"],
"env": {
"OUTLINE_URL": "https://your-outline-instance.com",
"OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx"
}
}
}
}
</details>
<details> <summary>Windsurf</summary>
Add to Windsurf MCP settings (~/.codeium/windsurf/mcp_config.json):
{
"mcpServers": {
"outline": {
"command": "npx",
"args": ["-y", "outline-smart-mcp"],
"env": {
"OUTLINE_URL": "https://your-outline-instance.com",
"OUTLINE_API_TOKEN": "ol_api_xxxxxxxxxxxxx"
}
}
}
}
</details>
<details> <summary>ChatGPT Desktop</summary>
ChatGPT supports MCP through its desktop app. Add the server in Settings → MCP Servers with:
- Command:
npx - Arguments:
-y outline-smart-mcp - Environment variables as shown above
</details>
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-smart-mcp"],
"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.
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