Rhylthyme MCP Server

Rhylthyme MCP server

A Model Context Protocol server for schedules that a person executes: cooking several dishes so they finish together, running a bench protocol with overlapping incubations, calling an event, running a workout. An agent describes the process, the server validates and analyzes the resulting program, and publishes it as a live timeline on rhylthyme.com that the person follows on their phone.

This repository is the source of the server that runs at mcp.rhylthyme.com. It is the same code as mcp-api/ in the rhylthyme-server application, copied here with the static assets it needs so it can be read, tested and self-hosted.

Try it: ask for a workout

Connect the server (in Claude Code, /plugin marketplace add rhylthyme/rhylthyme-mcp then /plugin install rhylthyme@rhylthyme; anywhere else, add https://mcp.rhylthyme.com/gym/mcp as a connector), then say what you want in plain words:

Two of us in a garage gym: one kettlebell, one pull-up bar, one jump rope. Thirty minutes, two rounds, and nobody stands around waiting for equipment. Make it a Rhylthyme timeline.

You write no JSON. The assistant does, and the server keeps it honest. With that prompt Claude made three tool calls:

                0                       15m                    30m
Alex           │░Warm-…░▒S…▒░Pu…░▒Ju…▒░░░▒Sw…▒░Pu…░▒Ju…▒░░░▒St…▒│
Sam            │░Warm-…░▒P…▒░Ju…░▒Sw…▒░░░▒Pu…▒░Ju…░▒Sw…▒░░░▒St…▒│

Ask "show me a picture" and preview_timeline returns an image in the chat. For one coloured by station, which makes the rotation obvious, save the program the assistant wrote (ours is examples/recipe/garage-circuit.json) and run:

npx -y github:rhylthyme/rhylthyme-timeline garage-circuit.json -o garage-circuit.png \
  --style web --palette tableau --color-by task

Then push on it: "add a third person", "we only have 20 minutes", "swap the rope for burpees". The assistant edits the program and the server checks it again.

This repository and rhylthyme-cli-runner

Two repositories do related things and are easy to confuse. This one is the server an AI assistant talks to. rhylthyme-cli-runner is the command a person types.

How they fit together: the command-line tool is one of this server's clients. rhylthyme analyze, publish, generate and mcp-test are MCP calls to mcp.rhylthyme.com; rhylthyme validate, run, runs and calibrate never touch the network. Each has its own validator for the same program schema (JavaScript here, Python there), so a program is checked again when it is published.

Use this repository to connect an assistant, to read or self-host the server, or to change a tool. Use rhylthyme-cli-runner if you have a program file and a terminal, want timers in the terminal, or keep run records.

Two names to keep apart: rhylthyme-mcp on PyPI is this server's stdio bridge (command rhylthyme-mcp, source in python/); rhylthyme-cli-runner on PyPI is the command-line tool (command rhylthyme). The program format itself is defined in rhylthyme-spec, with examples in rhylthyme-examples.

Endpoints

Transport: Streamable HTTP, stateless. No sign-in is needed for the public catalog or the pure tools; account tools use the person's Rhylthyme account through OAuth 2.1, or a pasted token from the login tool in clients without OAuth. Server instructions describing the workflow are sent at initialize.

Quickstart: timelines from the command line

The rhylthyme CLI can drive this server directly: describe what you need in plain language and get back a live timeline URL, a program file, or both.

pip install rhylthyme                        # Python 3.12+
rhylthyme login                              # opens rhylthyme.com in your browser
rhylthyme generate "roast chicken, potatoes and green beans for 6" \
    -e kitchen --by 19:00 --with "one oven, four burners, one cook"

login signs you in through the browser and hands the session back to a one-shot listener on 127.0.0.1. It is stored in ~/.config/rhylthyme/credentials.json (mode 0600) and renews itself, so you only log in once. generate then calls two tools on this server:

1. import_text on the endpoint for -e (/kitchen/mcp, /lab/mcp, …) turns the request into a validated multi-track program. It runs four model turns server-side, which is why it needs a sign-in; it takes 20–60 seconds and is capped per day.
2. visualize_schedule publishes that program and returns the live-timeline URL on the matching subdomain.

It prints the ASCII Gantt, the itinerary and the URL. More examples:

# A lab protocol from a file; save the program and run it in the terminal
rhylthyme generate -e lab -f western_blot.txt -o blot.json --run

# Pipe a run sheet in; print only the URL
pbpaste | rhylthyme generate -e events --by "doors at 18:30" -q

# Program JSON only, no published timeline; machine-readable output
rhylthyme generate -e gym "45 minute upper-body circuit, two people, one bench" --no-publish --json

To check a server (this one, or your own deployment) end to end:

rhylthyme mcp-test                                   # all five hosted endpoints, read-only
rhylthyme mcp-test --url http://localhost:3000/mcp -e generic --publish

rhylthyme whoami shows the stored sign-in; rhylthyme logout forgets it. On a machine without a browser, set RHYLTHYME_TOKEN to an access token from https://www.rhylthyme.com/mcp/auth (it lasts about an hour), or run rhylthyme login --token <token>. RHYLTHYME_MCP_URL points the CLI at a self-hosted server.

Connect

Claude Code

claude mcp add --transport http rhylthyme https://mcp.rhylthyme.com/mcp
claude mcp add --transport http rhylthyme-kitchen https://mcp.rhylthyme.com/kitchen/mcp

Claude Desktop / claude.ai: Settings → Connectors → Add custom connector → paste one of the URLs above. Public tools work immediately; run login only to save to your own account.

Claude Code plugin (the hosted server plus a skill that teaches Claude to author, validate and analyze schedules):

/plugin marketplace add rhylthyme/rhylthyme-mcp
/plugin install rhylthyme@rhylthyme

ChatGPT: Settings → Apps & Connectors → Advanced settings → turn on Developer mode, then Create a connector with one of the URLs above as the MCP server URL. Without a connector ChatGPT cannot call these tools and falls back to browsing the website.

Cursor (.cursor/mcp.json):

{ "mcpServers": { "rhylthyme": { "url": "https://mcp.rhylthyme.com/kitchen/mcp" } } }

Claude API (MCP connector, one request):

import anthropic
client = anthropic.Anthropic()
resp = client.beta.messages.create(
    model="claude-opus-5", max_tokens=16000,
    betas=["mcp-client-2025-11-20"],
    mcp_servers=[{"type": "url", "url": "https://mcp.rhylthyme.com/kitchen/mcp", "name": "rhylthyme"}],
    tools=[{"type": "mcp_toolset", "mcp_server_name": "rhylthyme"}],
    messages=[{"role": "user", "content": "Plan Thanksgiving for 8 with one oven, dinner at 6pm."}],
)

Reviewing an import. review_program (an account tool) has a model read an imported program against its source and return findings: wrong durations, dropped steps, bad ordering, a total that disagrees with the source. Call it after import_from_source or import_text, apply what it says, and validate again.

Clients that can only launch a command: pip install rhylthyme-mcp gives a rhylthyme-mcp command, a stdio bridge that passes every request through to the hosted server (source in python/):

{ "mcpServers": { "rhylthyme": { "command": "rhylthyme-mcp", "args": ["kitchen"] } } }

No MCP client at all (an agent with a shell, a script): the server is stateless, so one POST works with no handshake and no account.

curl -s https://mcp.rhylthyme.com/mcp \
  -H 'Content-Type: application/json' -H 'Accept: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
       "params":{"name":"validate_program","arguments":{"program":{"programId":"x","name":"x","tracks":[]}}}}'

visualize_schedule called the same way returns the live-timeline URL in result.structuredContent.url. Or use the CLI in the quickstart above.

Tools

Annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) are set on every tool; four tools also declare an outputSchema and return structuredContent. Failures set isError and say what to do next.

Resources and prompt

• rhylthyme://schema/program: the program JSON Schema (0.3.0-alpha)
• rhylthyme://guide/authoring: one-page authoring rules, trigger vocabulary, how to make tracks finish together, repeated work (replicates, per-instance instances: "each" chains, "all" barriers and maxInFlight), choice branching
• rhylthyme://guide/tools: the long form of every tool description. The tool list itself is kept to about 3,600 tokens so it is cheap to keep connected
• rhylthyme://examples/{breakfast_schedule, lab_experiment, stir_fry_with_choice, hiit_cardio_workout, corporate_presentation, cookies_three_trays}: complete valid programs (cookies_three_trays is the 0.3.0-alpha per-instance / in-flight worked example)
• prompt plan_schedule(goal, finishAt?, constraints?): walks the model through search → build → validate → analyze → visualize, and names replicates / instances / maxInFlight in its constraints step

What a program looks like

{
  "schemaVersion": "0.1.0",
  "programId": "eggs-and-toast",
  "name": "Eggs and toast",
  "tracks": [
    { "trackId": "eggs", "name": "Eggs", "steps": [
      { "stepId": "whisk", "name": "Whisk", "task": "prep",
        "duration": { "type": "fixed", "seconds": 60 },
        "startTrigger": { "type": "programStart" } },
      { "stepId": "cook", "name": "Cook", "task": "stove",
        "duration": { "type": "variable", "minSeconds": 120, "maxSeconds": 240, "defaultSeconds": 180 },
        "startTrigger": { "type": "afterStep", "stepId": "whisk" } } ] },
    { "trackId": "toast", "name": "Toast", "steps": [
      { "stepId": "toast", "name": "Toast", "task": "toaster",
        "duration": { "type": "fixed", "seconds": 180 },
        "startTrigger": { "type": "afterStep", "stepId": "cook", "event": "start", "offsetSeconds": 60 } } ] }
  ],
  "resourceConstraints": [
    { "task": "prep", "maxConcurrent": 1 },
    { "task": "stove", "maxConcurrent": 2 },
    { "task": "toaster", "maxConcurrent": 1 }
  ]
}

Steps in one track run sequentially; parallel work goes in separate tracks; every task needs a resource constraint; durations and offsets take seconds or strings like "5m". Triggers: programStart, programStartOffset, afterStep (end or event: "start", signed offset), afterStepWithBuffer, manual, onAbort, or {logic: all|any, triggers}. Durations: fixed, variable (ended early by the executor), indefinite (ended by the executor).

Self-hosting

git clone https://github.com/rhylthyme/rhylthyme-mcp
cd rhylthyme-mcp
npm install            # Node 20 or newer
npm test                 # SDK in-memory + HTTP entry-point tests, no network
PORT=3000 npm start      # http://localhost:3000/mcp and the four vertical paths

Docker: docker build -t rhylthyme-mcp . && docker run -p 3000:3000 rhylthyme-mcp. Vercel: vercel in the repository root; vercel.json rewrites the endpoint paths to the function.

What self-hosting does and does not give you: validation, timing analysis, the renderer, resources and prompts run in your process. Catalog search, sharing (visualize_schedule), imports and account tools call the public API at https://www.rhylthyme.com (API_BASE in mcp-api/index.js), so those still depend on the hosted service. The PNG preview route /api/og/timeline.png additionally needs SUPABASE_URL and SUPABASE_ANON_KEY for read access to shared programs; nothing else does.

Layout

• mcp-api/index.js: tool, resource and prompt registration; vertical detection; OG-image route; Vercel handler
• mcp-api/schedule.js: validator and analyzer (pure)
• static/js/timeline-render.js: timing engine and SVG Gantt (also published as @rhylthyme/timeline)
• static/schema/, static/examples/: the resources
• src/index.js: standalone HTTP runner
• mcp-api/server.json: MCP registry manifest
• .claude-plugin/marketplace.json, plugins/rhylthyme/: the Claude plugin marketplace and plugin (claude plugin validate .); the skill in it is a checked copy of rhylthyme-cli-runner/skills/rhylthyme
• python/: the rhylthyme-mcp PyPI package, a stdio bridge to the hosted server (cd python && PYTHONPATH=src pytest tests)

Known limitations

• login hands the user a URL and expects a pasted, short-lived access token that then travels as a tool argument; it is outside MCP's OAuth 2.1 flow. Hosts that require OAuth for authenticated servers can still use every public tool.
• search_public_recipes searches one environment at a time; the generic endpoint defaults to kitchen.
• Tool annotations are self-declared hints; hosts may ignore them.

License

Apache-2.0, like the rest of Rhylthyme. (This repository was MIT until September 2026.)