Which integrations are available for this server?

Enables document management, search, collections, comments, and collaboration features within Outline wiki instances. Includes optional AI-powered capabilities like RAG-based Q&A, semantic search, document summarization, tag suggestions, and diagram generation.

How do I use Outline Wiki MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Outline Wiki MCP Server summarize the Q4 planning document for me" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Outline Wiki MCP Server

by huiseo

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Outline Wiki MCP Server

English | 한국어 | 日本語 | 中文

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

Related MCP server: Outline MCP Server

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-smart-mcp"],
      "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-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.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-smart-mcp"],
      "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-smart-mcp"],
      "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-smart-mcp"],
      "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-smart-mcp
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-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.

Available Tools

37 tools

add_commentC

Add a comment to a document. Supports replies.

Inputs: documentId (required), text (required), parentCommentId.

archive_documentD

Archive a document.

Inputs: documentId (required).

ask_wikiC

Ask a question and get an answer based on wiki content using RAG.

Inputs: question (required).

batch_archive_documentsC

Archive multiple documents at once.

Inputs: documentIds (required).

batch_create_documentsC

Create multiple documents at once.

Inputs: documents (required).

batch_delete_documentsC

Delete multiple documents at once.

Inputs: documentIds (required), permanent.

batch_move_documentsC

Move multiple documents at once.

Inputs: documentIds (required), collectionId, parentDocumentId.

batch_update_documentsC

Update multiple documents at once.

Inputs: updates (required).

create_collectionC

Create a new collection.

Inputs: name (required), description, color.

create_documentD

Create a new document.

Inputs: title (required), collectionId (required), text, parentDocumentId, +1 more.

delete_collectionB

Delete a collection. All documents in the collection will also be deleted.

Inputs: collectionId (required).

delete_documentB

Delete a document. If permanent=true, permanently delete; otherwise move to trash.

Inputs: documentId (required), permanent.

export_all_collectionsC

Export all collections.

Inputs: format.

export_collectionC

Export a collection.

Inputs: collectionId (required), format.

export_documentC

Export document in Markdown format.

Inputs: documentId (required).

find_relatedC

Find documents semantically related to a specific document.

Inputs: documentId (required), limit.

generate_diagramC

Generate a Mermaid diagram from a text description.

Inputs: description (required).

get_collection_structureC

Get document hierarchy within a collection.

Inputs: collectionId (required).

get_commentC

Get details of a specific comment.

Inputs: commentId (required).

get_documentC

Get full document content by document ID.

Inputs: documentId (required).

get_document_backlinksC

Find other documents linking to this document.

Inputs: documentId (required).

get_document_id_from_titleC

Find document ID by title.

Inputs: query (required), collectionId.

list_archived_documentsC

Get list of archived documents.

Inputs: limit.

list_collectionsC

Get list of all collections.

Inputs: no named parameters.

list_document_commentsC

Get list of comments on a document.

Inputs: documentId (required), limit, offset.

list_recent_documentsC

Get list of recently modified documents.

Inputs: limit.

list_trashC

Get list of documents in trash.

Inputs: limit.

move_documentC

Move document to another collection or under a parent document.

Inputs: documentId (required), collectionId, parentDocumentId.

restore_documentC

Restore a document from trash.

Inputs: documentId (required).

search_documentsC

Search documents by keyword. Supports pagination.

Inputs: query (required), collectionId, limit, offset.

smart_statusB

Check if smart features are enabled and get index statistics.

Inputs: no named parameters.

suggest_tagsC

Get AI-suggested tags for a document based on its content.

Inputs: documentId (required).

summarize_documentC

Generate an AI-powered summary of a document.

Inputs: documentId (required), language.

sync_knowledgeB

Sync documents to vector store for AI-powered search. Run this before using ask_wiki.

Inputs: collectionId.

unarchive_documentB

Restore an archived document.

Inputs: documentId (required).

update_collectionC

Update collection information.

Inputs: collectionId (required), name, description, color.

update_documentC

Update an existing document. Can append content with append mode.

Inputs: documentId (required), title, text, append.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.2/5.0

Scored 2026-04-18 07:45 across 37 tools

Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count3/5

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.

Completeness5/5

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.

Maintenance

ActivityInactive

ResponsivenessNo recent community issues

Resources

Related MCP Connectors

ragie
com.mcparmory
Ingest, manage, and retrieve documents for RAG-powered AI applications
RAG Systems Databases Knowledge & Memory
2
https://mcp.mcparmory.com/ragie
Kumbuka
ai.kumbuka
Governed, auditable knowledge your team curates for its AI assistants, self-hostable
Knowledge & Memory RAG Systems
21
https://mcp.kumbuka.ai/mcp
agentbay-mcpA
io.github.thomasjumper
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
Knowledge & Memory Autonomous Agents Agent Orchestration
21
https://www.aiagentsbay.com/api/mcp
Brains
io.github.brainsforai
Personal wiki and memory layer for AI assistants. Persistent, structured memory across sessions.
Knowledge & Memory Note Taking AI & Machine Learning
2
https://lets.usebrains.app/mcp

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Outline Wiki MCP Server

Why This Server?

Example Usage

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

Available Tools

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Outline Wiki MCP Server

Outline MCP Server

mcp-outline

mcp-outline