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Workflows MCP Server

by cyanheadsversion 0.5.0i★ –iRuns on your computer
Registry nameio.github.cyanheads/workflows-mcp-server

Install

Overview

Description from the maker (original English)

Store, query, and create YAML workflow playbooks for LLM agents.

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.

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: WORKFLOWS_DIR, GLOBAL_INSTRUCTIONS_PATH, WATCHER_DEBOUNCE_MS, MCP_LOG_LEVEL

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "workflows": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/workflows-mcp-server"
      ],
      "env": {
        "WORKFLOWS_DIR": "your-value",
        "GLOBAL_INSTRUCTIONS_PATH": "your-value",
        "WATCHER_DEBOUNCE_MS": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add workflows --env WORKFLOWS_DIR=your-value --env GLOBAL_INSTRUCTIONS_PATH=your-value --env WATCHER_DEBOUNCE_MS=your-value --env MCP_LOG_LEVEL=your-value -- npx -y @cyanheads/workflows-mcp-server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "workflows": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/workflows-mcp-server"
      ],
      "env": {
        "WORKFLOWS_DIR": "your-value",
        "GLOBAL_INSTRUCTIONS_PATH": "your-value",
        "WATCHER_DEBOUNCE_MS": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "workflows": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/workflows-mcp-server"
      ],
      "env": {
        "WORKFLOWS_DIR": "your-value",
        "GLOBAL_INSTRUCTIONS_PATH": "your-value",
        "WATCHER_DEBOUNCE_MS": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

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

  • WORKFLOWS_DIR env
    Absolute or relative path to the workflows root directory.
  • GLOBAL_INSTRUCTIONS_PATH env
    Path to the global instructions markdown file. Derives from WORKFLOWS_DIR when not set.
  • WATCHER_DEBOUNCE_MS env
    Milliseconds to debounce filesystem change events before rebuilding the index.
  • MCP_LOG_LEVEL env
    Sets the minimum log level for output (e.g., 'debug', 'info', 'warn').

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 cyanheads, 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 7254 servers in this category
  • Published to the registry more recently than 80% of the other 7254 servers in this category
  • Basic checks equal to or better than 100% of the other 7254 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 Workflows MCP Server 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

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 (0.5.0) reached the registry 9 days ago.

Which apps can use it?

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

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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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
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Codebase Memory

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

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

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

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

@cyanheads/workflows-mcp-server Store, query, and create YAML workflow playbooks for LLM agents via MCP. STDIO or Streamable HTTP. 5 Tools


Overview

A declarative workflow library for LLM agents, backed by local YAML files. Store, list, and retrieve named, versioned multi-step playbooks — each a sequence of MCP server/tool calls — for permanent reuse or one-shot temporary runs. Edits to the YAML files are picked up automatically.

Tools
ToolDescription
workflow_listList all permanent workflows in the index, with optional keyword, category, and tag filters.
workflow_getRetrieve a complete workflow definition by name, with the library's global instructions included.
workflow_createWrite a new permanent workflow YAML to the library.
workflow_create_tempWrite a temporary workflow draft, indexed but excluded from list results, kept until deleted.
workflow_deleteRemove a permanent workflow or a temporary draft by name and optional version, after the user confirms the resolved target.

Capability reference

workflow_list tool
  • Optional query (name and description), category (substring), and tags (all must match) filters, case-insensitive; temporary drafts are never listed
  • Sorted by name, then highest version first; an empty result carries a notice echoing the applied filters
  • includeTools: true adds each workflow's unique server/tool pairs

workflow_get tool
  • name plus an optional semver version; omit version for the highest available, drafts included
  • Returns the full workflow, its source (permanent or temp), and globalInstructions from global_instructions.md (null when absent); fails with not_found or version_not_found
  • Template placeholders such as {{input.foo}} come back verbatim — the server never interpolates them

workflow_create tool
  • name, semver version, description, author, category, and steps (plus optional tags); stored as one file per name@version under categories/ /, with created and updated dates stamped
  • Returns the key (name@version) and filePath; fails with already_exists when a permanent workflow or a draft holds the key, invalid_input, or write_failed

workflow_create_temp tool
  • The workflow_create fields minus category; stored under temp/, retrievable with workflow_get, never listed, and kept until workflow_delete removes it
  • status is created, or overwritten when it replaced the draft of the same key (keeping that draft's created_date); a key held by a permanent workflow fails with already_exists

workflow_delete tool
  • name plus an optional version (omitted: the highest across permanent workflows and drafts); the user confirms the resolved name@version, source, and file before anything is deleted, so a client without elicitation cannot delete
  • Returns the deleted workflow's source, plus a notice when another file declaring the same key now takes its place; fails with cancelled, confirmation_invalid (a prompt never issued, already answered, older than 10 minutes, or issued to another caller), target_changed (the file or its content changed after the user saw it), or not_found

Features

Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.

Workflow library:

  • YAML files under categories/ and temp/ are validated at index time; an invalid file is skipped and logged, never crashes the server
  • In-memory index keyed by name@version, read from each file's content rather than its name and kept fresh by a debounced recursive watcher; a permanent workflow outranks a draft with the same key
  • Versions are canonical semver everywhere: a leading v, surrounding whitespace, and build metadata are dropped, so v1.0.0+build.5 is stored, keyed, and looked up as 1.0.0
  • Creates and deletes run one at a time, so each existence check holds until its write lands; filenames carry a hash of name@version, so keys whose slugs coincide never share a file
  • An _index.json snapshot is written on every rebuild for external tooling and debugging

Agent-friendly output:

  • Discriminated output — source: "permanent" | "temp" on every workflow_get response and typed reason codes (not_found, version_not_found, already_exists, cancelled, confirmation_invalid, target_changed, index_unavailable, …) on failures, so callers branch on data instead of parsing error strings
  • No extra round trip — workflow_get always returns globalInstructions alongside the workflow definition in the same response
  • Response shaping — workflow_list's optional includeTools flag pre-derives the unique server/tool pairs used by a workflow, and an empty result echoes the applied filters with a broadening hint instead of returning nothing

Getting started

No API keys required. The server reads from a local workflows-yaml/ directory by default.

Add the following to your MCP client configuration file:

{

"mcpServers": { "workflows-mcp-server": { "type": "stdio", "command": "bunx", "args": ["@cyanheads/workflows-mcp-server@latest"], "env": { "MCP_TRANSPORT_TYPE": "stdio", "WORKFLOWS_DIR": "/absolute/path/to/your/workflows-yaml" } } } }

Or with npx (no Bun required):

{

"mcpServers": { "workflows-mcp-server": { "type": "stdio", "command": "npx", "args": ["-y", "@cyanheads/workflows-mcp-server@latest"], "env": { "MCP_TRANSPORT_TYPE": "stdio", "WORKFLOWS_DIR": "/absolute/path/to/your/workflows-yaml" } } } }

Or with Docker:

{

"mcpServers": { "workflows-mcp-server": { "type": "stdio", "command": "docker", "args": [ "run", "-i", "--rm", "-e", "MCP_TRANSPORT_TYPE=stdio", "-v", "/absolute/path/to/your/workflows-yaml:/workflows-yaml", "-e", "WORKFLOWS_DIR=/workflows-yaml", "ghcr.io/cyanheads/workflows-mcp-server:latest" ] } } }

For Streamable HTTP, set the transport and start the server:

MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 bun run start:http

Server listens at http://localhost:3010/mcp

Seed workflows

The repository ships a workflows-yaml/ directory with example workflows organized under categories/. These are ready to use as a starting point. The workflows-yaml/global_instructions.md file contains instructions the server includes in every workflow_get response (the globalInstructions field) — edit it to set global guidance for your agent.

Prerequisites
  • Bun v1.4.0 or higher (or Node.js v24+).
  • A local directory containing YAML workflow files (or use the bundled workflows-yaml/ seed).
Installation
  1. Clone the repository:
git clone https://github.com/cyanheads/workflows-mcp-server.git
  1. Navigate into the directory:
cd workflows-mcp-server
  1. Install dependencies:
bun install
  1. Configure environment:
cp .env.example .env

edit .env if needed — most settings have defaults


Configuration

VariableDescriptionDefault
WORKFLOWS_DIRAbsolute or relative path to the workflows root directory../workflows-yaml
GLOBAL_INSTRUCTIONS_PATHPath to the global instructions markdown file. Derives from WORKFLOWS_DIR when not set. /global_instructions.md
WATCHER_DEBOUNCE_MSInteger milliseconds (0–2147483647) to debounce filesystem change events before rebuilding the index.500
MCP_TRANSPORT_TYPETransport: stdio or http.stdio
MCP_HTTP_PORTPort for HTTP server.3010
MCP_SESSION_MODEHTTP sessions: auto or stateful. workflow_delete's confirmation prompt needs a live session, so HTTP startup with stateless fails with a configuration error. Ignored over stdio.stateful, declared in src/index.ts
MCP_AUTH_MODEAuth mode: none, jwt, or oauth.none
MCP_REQUEST_STATE_KEYSeals the requestState a confirmation round carries (≥ 32 bytes, the same on every instance, e.g. openssl rand -base64 32); any state the server did not seal is rejected before the handler runs. workflow_delete's round carries its confirmation id, so set it for HTTP deployments.unset
MCP_LOG_LEVELLog level (RFC 5424).info
LOG_TOOL_FAILURE_PAYLOADSLog each failed tool call's arguments and result, redacted by key name and capped at LOG_TOOL_FAILURE_PAYLOAD_MAX_BYTES (default 16384). A secret inside a free-form value is not redacted.false
OTEL_ENABLEDEnable OpenTelemetry instrumentation (spans, metrics, completion logs).false

See .env.example for the full list of optional overrides.


Running the server

Local development
  • Build and run:
  # One-time build

bun run rebuild

Run the built server

bun run start:stdio

or

bun run start:http

  • Run checks and tests:
  bun run devcheck   # Lint, format, typecheck, security

bun run test # Vitest test suite bun run lint:mcp # Validate MCP definitions against spec

Docker
docker build -t workflows-mcp-server .

docker run --rm \ -v /path/to/workflows-yaml:/workflows-yaml \ -e WORKFLOWS_DIR=/workflows-yaml \ -p 3010:3010 \ workflows-mcp-server

The Docker

Only the beginning is shown; read the rest in the repo

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