AppFlowy Cloud MCP Server

A Model Context Protocol (MCP) server for interacting with AppFlowy Cloud API, providing tools for workspace, database, and row operations.

Features

• Authentication: Login and refresh token management

• Workspace Operations: List all workspaces

• Database Operations: List databases, get database fields

• Row Operations: List rows, get row details, create rows, upsert rows

Authentication

The server uses in-memory token storage. To authenticate:

1. Use appflowy_login with your email and password

2. The tokens are stored automatically

3. Use appflowy_refresh_token when the access token expires

Available Tools

Authentication Tools

• appflowy_login(request: LoginRequest) - Login to AppFlowy Cloud

• appflowy_refresh_token(request: RefreshTokenRequest) - Refresh access token

Workspace Tools

• appflowy_list_workspaces() - List all workspaces

Database Tools

• appflowy_list_databases(workspace_id: str) - List databases in a workspace

• appflowy_get_database_fields(workspace_id: str, database_id: str) - Get database fields

Row Tools

• appflowy_list_rows(workspace_id: str, database_id: str) - List row IDs

• appflowy_get_row_details(workspace_id: str, database_id: str, row_ids: str, with_doc: bool = False) - Get row details

• appflowy_create_row(workspace_id: str, database_id: str, request: RowCreateRequest) - Create a new row

• appflowy_upsert_row(workspace_id: str, database_id: str, request: RowUpdateRequest) - Update or create row

Running the Server

uv run python main.py

Usage Example

1. Login:

request = LoginRequest(email="your@example.com", password="your_password")
response = appflowy_login(request)

2. List workspaces:

workspaces = appflowy_list_workspaces()

3. Get database fields:

fields = appflowy_get_database_fields("workspace_id", "database_id")

4. Create a row:

row_request = RowCreateRequest(cells={"Field_Name": "Value"}, document="Optional markdown")
result = appflowy_create_row("workspace_id", "database_id", row_request)

Note

The server maintains tokens in memory. For production use, consider adding persistent storage (Redis, database, etc.) and proper error handling.