Workato Dev MCP
Enables authoring and debugging Workato recipes from Claude by wrapping the Workato Developer REST API for recipe CRUD, start/stop, and job inspection.
README
Workato Dev MCP
A local MCP server that lets you author and debug Workato recipes from Claude (Code, Desktop, or any MCP client).
The official Workato Developer API MCP (app.workato.com/mcp) is management/read-only — it can't create or update recipe code or start/stop recipes. This server does, by wrapping the Workato Developer REST API operations a recipe developer actually needs.
Zero dependencies — standard library only, any Python 3.8+. No pip install.
Quick install (Claude Code)
From the repo, one command registers the server with Claude Code:
WORKATO_TOKEN=your-developer-api-token bash bin/install.sh
Or bootstrap from scratch (clone + register) with one line:
curl -fsSL https://raw.githubusercontent.com/krishnagutta/workato-dev-mcp/main/bin/quickstart.sh | bash
Then start a new Claude session and try: "list my Workato recipes".
Even simpler — project-scoped auto-detection
This repo ships a .mcp.json. If a teammate opens the repo folder in Claude Code with WORKATO_TOKEN exported in their shell, Claude Code detects the server automatically — no claude mcp add needed. Approve it once when prompted.
export WORKATO_TOKEN=your-developer-api-token # add to ~/.zshrc to persist
cd workato-dev-mcp
claude # Claude Code picks up .mcp.json
Prerequisites
- Python 3.8+ (
python3 --version) — already on macOS/Linux. - A Workato Developer API token — Workato → Workspace admin → API clients. The Recipe operator role is enough for recipe CRUD. Copy the token (starts with
wrkaus-). - For Claude Code: the
claudeCLI installed (only needed forbin/install.sh).
Manual setup (any MCP client)
If you'd rather wire it by hand (Claude Desktop, or pinning an absolute path):
{
"mcpServers": {
"workato-dev": {
"command": "python3",
"args": ["/absolute/path/to/workato-dev-mcp/server.py"],
"env": {
"WORKATO_TOKEN": "your-developer-api-token",
"WORKATO_API_BASE": "https://www.workato.com/api"
}
}
}
}
- Claude Desktop config:
~/Library/Application Support/Claude/claude_desktop_config.json(macOS). - Claude Code user scope:
~/.claude.json.
Restart the client, start a new chat, and you should see the workato-dev tools.
What it gives you (33 tools)
Recipes
| Tool | Purpose |
|---|---|
list_recipes / get_recipe / get_recipe_steps |
Find and inspect recipes (incl. the parsed code tree) |
create_recipe / update_recipe |
Author recipe code (JSON) |
start_recipe / stop_recipe |
Activate/deactivate (start = the validator) |
copy_recipe / delete_recipe |
Duplicate / remove |
list_recipe_versions |
Version history for tracking / rollback awareness |
list_jobs / get_job |
Debug — per-step input/output/error from job history |
Workspace & config
| Tool | Purpose |
|---|---|
whoami |
Confirm which workspace/user your token is in |
list_connections / list_folders / list_projects |
Browse for config wiring |
create_folder |
Create a folder (optionally nested) |
get_properties / upsert_properties |
Read/write account properties (config + feature flags) |
API Platform — Workato MCP servers
A Workato MCP server built on API Platform is an API collection exposed as MCP; its tools are API endpoints, each backed by a recipe. These tools let the dev MCP introspect that surface. (The AI-Hub-native MCP / Genie layer has no Developer API — manage it in the UI.)
| Tool | Purpose |
|---|---|
list_api_collections |
List API collections (each can be exposed as an MCP server) |
list_api_endpoints |
List a collection's endpoints — the MCP server's tools, with method/path/active/recipe |
list_api_clients |
List API clients (the credentialed consumers) |
list_api_access_profiles |
List access profiles (client ↔ collection scope bindings) |
enable_api_endpoint |
Activate an endpoint (turn a tool ON). Start its recipe first. Mutates a live MCP server. |
disable_api_endpoint |
Deactivate an endpoint (turn a tool OFF). Mutates a live MCP server. |
create_api_collection |
Create a collection to expose as an MCP server (endpoints are still added in the UI) |
Not yet covered — AI-Hub-native MCP servers. Workato documents a server-management API at
/api/mcp/mcp_servers(create/list servers,assign_tools, edit tool descriptions), but with the current Developer API token that path returns the HTML login page on bothwww/apphosts — i.e. the API client lacks MCP scope (or the feature isn't enabled on the plan). Grant the API client API-platform/MCP scope in the Workato UI and those tools become a quick follow-up. Endpoint enable/disable above works today because it lives on the standard/api_endpointsrouter.
Lookup & data tables
| Tool | Purpose |
|---|---|
list_lookup_tables / query_lookup_table |
Browse lookup tables; read rows (e.g. captured logs) |
add_lookup_table_row |
Append a row (capture/log writes) |
list_data_tables |
List Workato Data Tables |
Knowledge base (two-tier, like the Studio MCP)
| Tool | Purpose |
|---|---|
workato_recipe_tips |
Curated cheat sheet of recipe-authoring gotchas (the promoted tier) |
log_learning |
Append a newly discovered gotcha to learnings.md (the intake queue) |
get_learnings |
Read learnings.md back, optionally filtered by category |
Auth & data residency
WORKATO_TOKEN(required) — your personal Developer API token. Each dev uses their own; nothing is shared or hosted.WORKATO_API_BASE(optional) — defaults tohttps://www.workato.com/api(US). Set per your data center, e.g.https://app.eu.workato.com/api.
The recipe edit loop
get_recipe(id, include_code=true) # pull the code tree
→ edit the JSON in conversation
→ stop_recipe(id) # running recipes can't be updated
→ update_recipe(id, code=<json>)
→ start_recipe(id) # start = the compiler; read validation errors
→ list_jobs / get_job # after a test run, inspect real step I/O
Run workato_recipe_tips and get_learnings once before building — they capture the datapill format, the trigger extended_output_schema requirement, the HTTP string-body trick, custom-code schema gotchas, valid condition operands, and the job-log debugging pattern. These are the things that otherwise cost hours.
Capturing learnings (two-tier, like the Studio MCP)
The knowledge base grows as you use it:
learnings.md(repo root) is the intake queue — append-only, low-friction. When Claude discovers a gotcha that isn't already inworkato_recipe_tips, it callslog_learningto append a dated, categorized entry. Then commit the file so teammates inherit it.workato_recipe_tips(the_TIPSblock inserver.py) is the curated tier. During periodic review, raw learnings are promoted into it and marked**Status**: promotedinlearnings.md.
log_learning / get_learnings are pure local file operations — no Workato API call, no token needed. The file is anchored to the repo via __file__; override the location with WORKATO_LEARNINGS_PATH if needed.
Notes / limits
- This is a dev tool — it can create, edit, start/stop, and delete recipes. Use a token scoped to a dev/impl workspace; be careful with
delete_recipe. - It does not touch the AI Hub layer (adding tools to an MCP server, server instructions, MCP Apps, or a tool's param-schema refresh) — those remain manual in the Workato UI. After a recipe param-set change, the MCP client that consumes that tool needs an app restart to see the new schema.
- Sharing: commit this folder to an internal git repo; teammates clone and either run
bin/install.shor exportWORKATO_TOKENand let.mcp.jsonauto-detect it.
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