Shiftyasan Shift Scheduling

@shiftyasan/mcp-server

Model Context Protocol (MCP) server for the Shiftyasan public solver API. Lets AI agents (Claude Desktop, Cursor, Continue, etc.) call the shift-scheduling solver from any MCP-aware host.

Status: open beta — validate_shift_input, solve_shift, and get_solve_job

(async polling for large problems). Usage queries (get_usage) coming next.

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Most people no longer need this package

Shiftyasan now runs a remote MCP server, which is the recommended way to connect:

https://api.shiftyasan.com/mcp

Connecting from Claude.ai or ChatGPT opens a Shiftyasan sign-in page in your browser; approve it once and you are done. Revoke a connection any time from the dashboard under "Connected apps".

This package is still supported and existing setups keep working. Reach for it when you want the server to run locally — for example on a host that cannot reach the internet directly, or when you prefer to hold your own API key.

See the quickstart for the remote setup.

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What is Shiftyasan?

Shiftyasan is a SaaS that auto-generates work shifts for businesses (retail, hospitality, healthcare, etc.) using a constraint-optimization engine. The same solver is exposed as a public HTTP API at https://api.shiftyasan.com/v1/public/*. This MCP server is a thin client wrapper that turns the API into discoverable tools for AI agents.

Developer documentation — quickstart, the full list of supported constraints, and pricing — lives at [https://platform.shiftyasan.com](https://platform.shiftyasan.com) (Japanese and English).

Tools

The full SolveRequest / SolveResponse schema lives in the OpenAPI spec at GET /v1/public/openapi.json (base URL = SHIFTYASAN_BASE_URL, default https://api.shiftyasan.com).

Prompts

Both arguments (period, context) are optional, so it can be invoked bare. In Claude Code it shows up as /mcp__shiftyasan__plan_shift; other hosts surface prompts in their own UI.

Use it when you want the agent to interview you for the inputs rather than guessing them, or when a previous attempt produced a roster you could not check at a glance. The prompt tells the agent to render one row per person with the per-person totals on the right, which is what a shift manager reads first.

The server also sends workflow guidance in its initialize response (call validate_shift_input before solve_shift, poll get_solve_job on 202, how to read shortage markers and the infeasibility diagnosis). Hosts may add this to the model's system prompt; Claude Code does, Claude Desktop currently does not, which is why the same ordering rules also live in the tool descriptions.

Constraints the schema accepts but the solver does not apply yet

A few fields are accepted by the API and then dropped during translation, because the solver has no equivalent. validate_shift_input and solve_shift print an explicit warning listing exactly what was dropped, so an agent never reports them as honored.

Everything else in the schema is applied by the solver.

Install

Running locally requires Node.js 20 or newer. If you would rather not manage that, use the

remote server instead.

Use directly via npx (no global install needed):

npx -y @shiftyasan/mcp-server

Also listed in the MCP Registry as com.shiftyasan/mcp-server.

Or install globally:

npm install -g @shiftyasan/mcp-server

shiftyasan-mcp-server

Setup

1. Get an API key

Issue an sk_live_... key in the self-service dashboard: [https://platform.shiftyasan.com/dashboard/](https://platform.shiftyasan.com/dashboard/) (your existing Shiftyasan account works; sign-up is also available). If anything goes wrong, email (Japanese or English).

Treat the token like a password: it grants access to your solver quota.

Beta note: you may receive a base URL different from the default —

set it via SHIFTYASAN_BASE_URL (see below).

2. Configure your MCP host

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{

"mcpServers": { "shiftyasan": { "command": "npx", "args": ["-y", "@shiftyasan/mcp-server"], "env": { "SHIFTYASAN_API_KEY": "sk_live_..." } } } }

Restart Claude Desktop. The shiftyasan server appears in the tools menu and exposes validate_shift_input, solve_shift, and get_solve_job.

Claude Code

claude mcp add shiftyasan -e SHIFTYASAN_API_KEY=sk_live_... -- npx -y @shiftyasan/mcp-server

(Add -e SHIFTYASAN_BASE_URL=... if you were given a beta base URL.)

Cursor / Continue / other MCP hosts

Add to your MCP server config in the same shape (command + args + env). Refer to your host's docs for the exact config file path.

Using from ChatGPT

ChatGPT cannot spawn local stdio MCP servers like this package, so use the HTTP API directly through a Custom GPT with Actions (the OpenAPI spec is designed to be Actions-compatible — fully inlined schemas, no external refs):

1. ChatGPT → My GPTs → Create a GPT → Configure → Actions → Import from URL, and enter /v1/public/openapi.json (base URL = the one you received with your API key; default https://api.shiftyasan.com).
2. If you were given a beta base URL, also edit the imported schema's servers[0].url to /v1/public.
3. Authentication → API Key → Auth Type Bearer → paste your sk_live_... token.
4. Suggested GPT instructions:

You can build optimized work shift schedules with the Shiftyasan actions.

Always call the validate action first (free), then solve. Large problems

return 202 with a job_id — poll the job endpoint every ~15 seconds until

the status is "completed" or "failed".

Notes: creating custom GPTs requires a paid ChatGPT plan, and the API key is stored inside the GPT — do not share that GPT publicly.

ChatGPT's MCP connectors only support hosted MCP endpoints (Streamable HTTP), not local stdio processes. A hosted MCP endpoint is on our roadmap; until then, use Actions as above.

Environment variables

Example session

In Claude Desktop, after configuring:

You: Schedule 3 employees over the first week of June across morning and

evening shifts. Use Shiftyasan.

Claude will discover the tools, call validate_shift_input to confirm the payload it constructed is acceptable, then call solve_shift to get the assignment. Errors from the API (RFC 7807) are surfaced inline so Claude can self-correct (e.g., "staffing_demand length must equal schedule_days").

Pricing

The open beta is free. Each API key comes with a free usage quota (solve_shift consumes units per call; validate_shift_input is always free). Check your remaining quota with GET /v1/public/usage using your key. When you run out, email to get more.

Paid plans are planned after the beta. The MCP server itself never charges; all metering happens against your SHIFTYASAN_API_KEY on the API side.

Local development

git clone https://github.com/shiftyasan/mcp-server.git

cd mcp-server npm install npm run build npm test

To run against a local gateway:

SHIFTYASAN_API_KEY=sk_test_... \

SHIFTYASAN_BASE_URL=http://localhost:8080 \ npm run dev

Test interactively with the MCP inspector:

npx @modelcontextprotocol/inspector node dist/index.js

Reporting issues

• MCP server bugs / requests: https://github.com/shiftyasan/mcp-server/issues
• Underlying API issues: contact

License

MIT — see LICENSE.