AppFlowy MCP
An MCP server for AppFlowy Cloud that enables workspace, space, page, trash, favorite, and page-content management.
README
AppFlowy MCP
An MCP server for AppFlowy. This fork adds workspace folder, space, page, trash, favorite, and basic page-content tools on top of the original workspace/database/row tools.
Requirements
- Python 3.14
- uv
- AppFlowy account credentials
Configure In Codex
codex mcp add appflowy -- uvx appflowy-mcp --env APPFLOWY_EMAIL="your-email" --env APPFLOWY_PASSWORD="your-password"
Option 1: PyPI / uvx
Use this after the package is published to PyPI. This is the simplest setup for daily use.
Use uvx as the command:
uvx
Use these arguments:
appflowy-mcp
Option 2: Local Source / uv
Use this when developing the MCP locally or running directly from a cloned repository.
Use uv as the command:
uv
Use these arguments:
run
--project
D:\codes\MCP\Appflowy-MCP
D:\codes\MCP\Appflowy-MCP\main.py
Configure In Claude-code
claude mcp add appflowy -- uvx appflowy -e APPFLOWY_EMAIL=your-email -e APPFLOWY_PASSWORD=your-password
Environment Variables
Set these environment variables:
APPFLOWY_EMAIL=your-email@example.com
APPFLOWY_PASSWORD=your-password
With these variables set, tools automatically log in on first use. appflowy_login is still available when you want to provide credentials explicitly.
For self-hosted AppFlowy, also set the base URL:
APPFLOWY_BASE_URL=http://localhost:8000
If omitted, APPFLOWY_BASE_URL defaults to https://beta.appflowy.cloud.
AppFlowy Structure
Most write operations need both a workspace and a parent view:
workspace -> space -> page/database
To create a page inside a space, pass the workspace ID and use the space view_id as parent_view_id.
Tools
Authentication
appflowy_loginappflowy_refresh_token
Workspaces And Spaces
appflowy_list_workspacesappflowy_get_workspace_folderappflowy_list_spacesappflowy_create_spaceappflowy_update_space
Pages
appflowy_create_pageappflowy_get_pageappflowy_update_pageappflowy_move_page_to_trashappflowy_restore_page_from_trashappflowy_delete_page_from_trashappflowy_favorite_pageappflowy_list_trashappflowy_list_favorites
Page Content
appflowy_save_pageappflowy_append_page_contentappflowy_append_text_to_pageappflowy_append_blocks_to_pageappflowy_create_markdown_pageappflowy_append_markdown_to_pageappflowy_import_markdown_fileappflowy_import_markdown_directory
Page-content support covers appending new document blocks, creating pages from Markdown, and appending Markdown to existing pages. AppFlowy exposes a high-level append-block endpoint, but not a matching high-level REST endpoint for deleting or editing arbitrary existing blocks. Page-level deletion through trash is supported.
When saving AI answers, notes, summaries, or generated content into AppFlowy, use appflowy_save_page by default. Its content_format field defaults to markdown, so agents do not need to ask users to say "save as Markdown" every time. Set content_format to plain_text only when the user explicitly wants the content preserved as literal plain text.
Use appflowy_append_page_content by default when adding AI-generated content to an existing page. It also treats content as Markdown unless content_format is set to plain_text.
Example paragraph block:
{
"type": "paragraph",
"data": {
"delta": [
{
"insert": "Hello from MCP"
}
]
}
}
Example Markdown page:
{
"parent_view_id": "space-or-page-view-id",
"title": "Meeting Notes",
"content": "# Meeting Notes\n\n- [ ] Follow up\n- **Important** decision\n\n```python\nprint(\"hello\")\n```",
"content_format": "markdown"
}
Markdown conversion supports headings, paragraphs, dividers, bullet lists, numbered lists, todo lists, quotes, code blocks, image links, and inline bold, italic, strikethrough, code, and links.
Markdown Import
Use appflowy_import_markdown_file to import one local Markdown file as an AppFlowy page. Use appflowy_import_markdown_directory to recursively import a local folder tree.
Directory import maps local structure directly to AppFlowy:
local folder -> AppFlowy page
local subfolder -> AppFlowy subpage
local .md/.markdown file -> AppFlowy page
README.md or index.md becomes the content of its folder page instead of a separate child page. Other Markdown files in the same folder become child pages. Hidden folders plus .git, .hg, .svn, .idea, .vscode, node_modules, and __pycache__ are skipped.
Local image references are resolved relative to the Markdown file, uploaded to AppFlowy file storage, and replaced with AppFlowy file URLs:


Remote image URLs such as https://... are kept as-is. Missing local images are reported in the import result warnings, while other files continue importing.
Example directory import:
{
"parent_view_id": "space-or-page-view-id",
"path": "D:\\notes",
"upload_assets": true
}
Example single-file import:
{
"parent_view_id": "space-or-page-view-id",
"path": "D:\\notes\\MCP\\config.md",
"title": "MCP Config",
"upload_assets": true
}
Databases And Rows
appflowy_list_databasesappflowy_get_database_fieldsappflowy_list_rowsappflowy_get_row_detailsappflowy_create_rowappflowy_upsert_rowappflowy_get_updated_rows
Local Run
uv run appflowy-mcp
Publish To PyPI
Build and check the package:
uv build
uv publish --dry-run --trusted-publishing never
Publish with a PyPI API token:
$env:UV_PUBLISH_TOKEN="pypi-your-token"
uv publish --trusted-publishing never
Do not commit PyPI tokens or write them into project files.
Notes
- Tokens are stored in memory by the MCP server process.
APPFLOWY_EMAIL,APPFLOWY_PASSWORD, andAPPFLOWY_BASE_URLcan also be provided through a local.envfile.- Some page and space endpoints are implemented from AppFlowy source routes that are not present in the public OpenAPI document.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
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.