Outline Wiki MCP Server
# Outline Wiki MCP Server
[](https://www.npmjs.com/package/outline-smart-mcp)
[](https://opensource.org/licenses/MIT)
[English](README.md) | [한국어](README.ko.md) | [日本語](README.ja.md) | [中文](README.zh.md)
A Model Context Protocol (MCP) server that enables LLMs to interact with [Outline](https://www.getoutline.com/) 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](https://claude.ai/download) | ✅ | ✅ | ✅ |
| [Claude Code](https://docs.anthropic.com/en/docs/claude-code) | ✅ | ✅ | ✅ |
| [VS Code GitHub Copilot](https://code.visualstudio.com/) | ✅ | ✅ | ✅ |
| [Cursor](https://cursor.sh/) | ✅ | - | ✅ |
| [Windsurf](https://codeium.com/windsurf) | ✅ | - | - |
| [ChatGPT Desktop](https://chatgpt.com/) | ✅ | - | - |
## 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
1. Log in to your Outline instance
2. Go to **Settings** → **API**
3. Click **Create API Key**
4. 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`
```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:
```bash
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):
```json
{
"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.json` file is ignored for MCP servers. Use `~/.claude.json` or `.mcp.json` instead.
</details>
<details>
<summary>VS Code GitHub Copilot</summary>
Add to your VS Code settings (`.vscode/mcp.json`):
```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`):
```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`):
```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:
```json
{
"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
```bash
# 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
```bash
READ_ONLY=true
```
Restricts to read operations only: search, get, export, list operations, and all smart features.
### Disable Delete
```bash
DISABLE_DELETE=true
```
Blocks: `delete_document`, `delete_collection`, `batch_delete_documents`
## Development
```bash
# 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](LICENSE) for details.
## Links
- [Outline Wiki](https://www.getoutline.com/)
- [Outline API Docs](https://www.getoutline.com/developers)
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [MCP Clients](https://modelcontextprotocol.io/clients)
TDQS
Scored across 37 tools
Most tools have distinct purposes, but some overlap exists. For example, 'search_documents' and 'find_related' both involve document discovery, though 'find_related' is semantic. 'archive_document' and 'delete_document' (with permanent=false) both involve removal, but descriptions clarify differences. Overall, descriptions help, but a few tools could be confused without careful reading.
Tool names follow a highly consistent verb_noun pattern throughout, such as 'create_document', 'list_collections', 'update_document', and 'delete_collection'. All tools use snake_case, and verbs are predictable (e.g., add, archive, ask, batch, create, delete, export, get, list, move, restore, search, sync, unarchive, update). No deviations or mixed conventions are present.
With 37 tools, the count is borderline high for a wiki server, feeling heavy compared to typical well-scoped sets of 3-15 tools. While the tools cover extensive operations, it may overwhelm agents. However, given the domain's complexity, it's not extreme, but leans toward too many for optimal coherence.
The tool set provides complete CRUD/lifecycle coverage for documents and collections, including creation, reading, updating, deletion, archiving, restoration, and export. It also includes advanced features like AI-powered search, summarization, diagram generation, and batch operations. No obvious gaps exist; agents can handle all core wiki workflows without dead ends.