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Workflowy

by jbeshirversion 1.0.2i★ –iRuns on your computer
Registry nameio.github.jbeshir/workflowy-mcp

Install

Overview

Description from the maker (original English)

Search, read, create, and organize Workflowy nodes with breadcrumb context.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory
  • You need to fill in: WORKFLOWY_API_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: WORKFLOWY_API_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Download the maker’s .mcpb file

The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.

Run this in your terminal

Fill in the empty values before running it.

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • WORKFLOWY_API_TOKEN secret required env
    Workflowy API token from workflowy.com/api-key

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account jbeshir, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7258 servers in this category
  • Published to the registry more recently than 76% of the other 7258 servers in this category
  • Basic checks equal to or better than 100% of the other 7258 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Workflowy safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: WORKFLOWY_API_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.2) reached the registry 11 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

workflowy-mcp

An MCP server that provides full read/write access to Workflowy. Search, create, organize, move, and complete nodes from any MCP-compatible client such as Claude Desktop or Claude Code. The server communicates over stdio and caches Workflowy's export endpoint to stay within API rate limits.

Getting Started

Requirements
Configuration
VariableRequiredDescription
WORKFLOWY_API_TOKENYesYour Workflowy API token
WORKFLOWY_API_URLNoCustom API URL (default: https://workflowy.com)
Install from source

Requires Go 1.27.3+.

go install github.com/jbeshir/mcp-servers/workflowy/cmd/workflowy-mcp@latest
Docker
docker build -t workflowy-mcp ./workflowy

docker run -e WORKFLOWY_API_TOKEN= workflowy-mcp

Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{

"mcpServers": { "workflowy": { "command": "/path/to/workflowy-mcp", "env": { "WORKFLOWY_API_TOKEN": " " } } } }

Claude Code
claude mcp add workflowy -- env WORKFLOWY_API_TOKEN=<your-token> /path/to/workflowy-mcp

Tools

ToolDescription
search_nodesSearch nodes by keyword and/or completion date range (completed_after/completed_before, unix seconds) across name and note fields
get_nodeGet full details of a node by ID
list_childrenList child nodes of a parent, sorted by priority
create_nodeCreate a new node
update_nodeUpdate an existing node's properties
delete_nodeDelete a node
move_nodeMove a node to a different parent
complete_nodeMark a node as completed
uncomplete_nodeMark a node as not completed
list_targetsList system locations (home/inbox) and user shortcuts

Key Concepts

  • Nodes — The basic unit in Workflowy. Every bullet, heading, todo, and code block is a node. Nodes form a tree: each node can have children, and every node except the root has a parent.
  • Targets — Named system locations (home, inbox) and user-defined shortcuts. You can use target keys anywhere a parent ID is accepted, so you can create nodes in your inbox without knowing its UUID.
  • Layout modes — Each node has a display mode: bullets (default), todo, h1, h2, h3, code-block, or quote-block.
  • Breadcrumb paths — Search results include the full chain of ancestor names (e.g. Projects > Backend > Auth), giving context for where a node sits in the hierarchy.
  • Hierarchical completion — Completing a parent node implicitly completes all its children. The server understands this when filtering search results, so a child under a completed parent is treated as completed even if it has no completion timestamp of its own.

Architecture Overview

graph LR

Client["MCP Client"] Server["MCP Server 10 tools"] Cache["Export Cache TTL 60s+"] HTTP["HTTP Client Bearer token auth"] API["Workflowy REST API"]

Client -->|"JSON-RPC over stdio"| Server Server -->|"reads"| Cache Server -->|"writes"| HTTP Cache -->|"cache miss"| HTTP HTTP -->|"HTTPS"| API

The server has three internal layers:

  • MCP Server (internal/server/) — Registers 10 tools, parses arguments, formats JSON responses with breadcrumb paths.
  • Export Cache (internal/cache/) — TTL-based cache of the full node export. Uses double-checked locking (RWMutex) to coalesce concurrent fetches. Minimum TTL is 60 seconds to respect Workflowy's rate limit on the export endpoint.
  • HTTP Client (internal/client/) — Thin REST client. All requests use Bearer token authentication. Read operations go through the cache; write operations call the API directly and then invalidate the cache.

Data Flow

Read path (search, get, list)
sequenceDiagram

participant C as MCP Client participant S as MCP Server participant Ca as Export Cache participant H as HTTP Client participant A as Workflowy API

C->>S: search_nodes(query) S->>Ca: GetAllNodes() alt Cache hit (within TTL) Ca-->>S: Cached nodes else Cache miss or expired Ca->>H: ExportNodes() H->>A: GET /api/v1/nodes-export A-->>H: All nodes (JSON) H-->>Ca: []Node Ca-->>S: Fresh nodes end S-->>C: Matching nodes with breadcrumb paths

Write path (create, update, delete, move, complete)
sequenceDiagram

participant C as MCP Client participant S as MCP Server participant Ca as Export Cache participant H as HTTP Client participant A as Workflowy API

C->>S: create_node(name, parentId) S->>H: CreateNode(request) H->>A: POST /api/v1/nodes A-->>H: Created node ID H-->>S: CreateNodeResponse S->>Ca: Invalidate() S-->>C: "Created node with ID: ..."

Write operations bypass the cache entirely, call the Workflowy API directly, and then invalidate the cache so the next read fetches fresh data.

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