spark-mcp

!spark-mcp logo

spark-mcp

MCP server for the Spark Membership platform — a CRM used by hundreds of martial arts studios. Manage class scheduling, bookings, attendance, and more through any MCP client (e.g. Claude Code).

Built by reverse-engineering the Spark Membership mobile app API.

Quick Start (Docker)

Docker is the preferred way to run spark-mcp — no Python install needed.

1. Pull the image:

docker pull ghcr.io/aserper/spark-mcp:latest

2. Add to your Claude Code config (.mcp.json in your project root or ~/.claude/settings.json):

{
  "mcpServers": {
    "spark": {
      "type": "stdio",
      "command": "docker",
      "args": ["run", "--rm", "-i",
        "-e", "SPARK_EMAIL", "-e", "SPARK_PASSWORD", "-e", "SPARK_LOCATION_ID",
        "ghcr.io/aserper/spark-mcp"],
      "env": {
        "SPARK_EMAIL": "your-email@example.com",
        "SPARK_PASSWORD": "your-password",
        "SPARK_LOCATION_ID": "1234"
      }
    }
  }
}

3. Restart Claude Code and start asking about your classes.

Finding your Location ID

Every studio on Spark Membership has a numeric location ID. Use the included find_location.py script to look it up.

Search by state code:

# Docker
docker run --rm --entrypoint python ghcr.io/aserper/spark-mcp find_location.py MA

# Local
python find_location.py MA

Search by studio name:

# Docker
docker run --rm --entrypoint python ghcr.io/aserper/spark-mcp find_location.py "jiu jitsu"

# Local
python find_location.py natick

Interactive mode (lists countries, states, then locations):

# Docker
docker run --rm -it --entrypoint python ghcr.io/aserper/spark-mcp find_location.py

# Local
python find_location.py

Example output:

    ID  Name
    --  ----
  1588  Metrowest Academy of Jiu Jitsu (Natick)
  6218  Villaris Martial Arts of Natick (Natick)

Use the ID value as your SPARK_LOCATION_ID.

Tools

| Tool | Description | |------|-------------| | login | Authenticate with email, password, and location ID | | list_classes | List available classes for a given date | | my_classes | List classes you're currently enrolled in | | book_class | Book a class by roster ID and date | | cancel_booking | Cancel a class reservation | | join_waitlist | Join the waitlist for a full class | | get_waitlist | List classes you're on the waitlist for | | checkin | Check in to a class | | dashboard | Get the studio dashboard overview | | attendance | View attendance history | | announcements | Get studio announcements | | memberships | Get membership status |

Usage Examples

Once configured, you can ask Claude things like:

• "What classes are available this Saturday?"
• "Book me into the 9am Ninjas class on March 21"
• "What am I signed up for?"
• "Cancel my Saturday booking"
• "Show my attendance history"
• "Any new announcements from the studio?"

Alternative: Local Install

If you prefer not to use Docker:

git clone https://github.com/aserper/spark-mcp.git
cd spark-mcp
uv venv && source .venv/bin/activate
uv pip install -e .

Then configure Claude Code with:

{
  "mcpServers": {
    "spark": {
      "type": "stdio",
      "command": "/path/to/spark-mcp/.venv/bin/python",
      "args": ["-m", "spark_mcp"],
      "env": {
        "SPARK_EMAIL": "your-email@example.com",
        "SPARK_PASSWORD": "your-password",
        "SPARK_LOCATION_ID": "1234"
      }
    }
  }
}

Authentication

Credentials can be provided in three ways:

1. Environment variables (recommended) — set SPARK_EMAIL, SPARK_PASSWORD, and SPARK_LOCATION_ID in your MCP config. The server auto-authenticates on first tool call.
2. login tool — call it manually at runtime without any env vars.
3. Mix — set email/password in env vars and use login to switch locations.

Tokens are automatically refreshed when they expire.

API Reference

All endpoints hit https://mobileapi.sparkmembership.com/api/student/. Auth uses Bearer tokens with automatic refresh. See api-discovery.md for the full endpoint reference.

OpenClaw / Claude Code Skill (Optional)

For a higher-level, natural language interface, install the spark skill:

# Via mcporter
mcporter config import spark ./openclaw-skill/SKILL.md

# Or manually copy to your OpenClaw skills directory
cp -r openclaw-skill ~/.openclaw/skills/spark

Then use natural language commands:

spark who                          # Discover family members
spark book hailey thursday         # Book Hailey for next Thursday
spark bulk "ily saturdays 4 weeks" # Bulk book Saturdays
spark my-classes                   # Show current bookings

See openclaw-skill/SKILL.md for full documentation.

Requirements

• Docker (preferred), or Python 3.11+
• A Spark Membership account (through your studio's app)