Freeplay MCP Server

An MCP (Model Context Protocol) server that enables AI agents to interact with Freeplay, the ops platform for AI engineering teams.

Use it to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments to validate changes before deploying.

⚠️ EXPERIMENTAL

This MCP server is an experimental release and will change. Use at your own risk and keep an eye on what your agents are doing.

Current limitations:

• Does not support deployment operations or destructive deletion actions — use the Freeplay UI
• Uses your regular Freeplay API key (not specially scoped to limit access for agents)

Security warning: Because this uses your full API key, an agent could extract the key and formulate its own API calls outside the scope of the tools included with this MCP server, including destructive actions against your Freeplay account.

Additionally, all MCP servers share a security context within the host, enabling data exfiltration, prompt injection across tools, and cross-server data access.

Only use this with agents and MCP servers you fully trust.

---

Installation

Claude Code

If using Claude Code, it is recommended to use the freeplay-plugin, which includes skills and this MCP server: https://github.com/freeplayai/freeplay-plugin.

The simplest way to install only the Freeplay MCP server is via uvx:

claude mcp add freeplay -- uvx freeplay-mcp

Set your API key in your MCP client process:

export FREEPLAY_API_KEY="your-api-key"
export FREEPLAY_BASE_URL="https://app.freeplay.ai"

Start Claude Code and run /mcp to check installation.

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
   "mcpServers": {
      "freeplay": {
         "command": "uvx",
         "args": [
            "freeplay-mcp"
         ],
         "env": {
            "FREEPLAY_API_KEY": "your-api-key",
            "FREEPLAY_BASE_URL": "https://app.freeplay.ai"
         }
      }
   }
}

Docker

For containerized deployments:

1. Clone and build:

   git clone https://github.com/freeplayai/freeplay-mcp.git
   cd freeplay-mcp
   docker build -t freeplay-mcp .
   

2. Set your environment variables (in .env, then source it).

   export FREEPLAY_API_KEY="your-api-key"
   export FREEPLAY_BASE_URL="https://app.freeplay.ai"
   

3. Add to Claude Code:

   claude mcp add --transport stdio freeplay-mcp -- docker run -i --rm -e FREEPLAY_API_KEY=$FREEPLAY_API_KEY -e FREEPLAY_BASE_URL=$FREEPLAY_BASE_URL freeplay-mcp
   

For production deployments, consider using a hardened base image such as Chainguard or Distroless.

4. Start Claude Code and run /mcp to check installation.

Authentication

• API key passed via environment variable FREEPLAY_API_KEY
• All requests use Bearer token authentication
• Base URL configurable via FREEPLAY_BASE_URL (default: https://app.freeplay.ai)

Development

# Clone and install
git clone https://github.com/freeplayai/freeplay-mcp.git
cd freeplay-mcp
uv sync --group dev

# Lint (with auto-fix)
make lint

# Type check
make type-check

# Run both
make check

Using Docker

{
  "mcpServers": {
    "freeplay": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "FREEPLAY_API_KEY",
        "-e",
        "FREEPLAY_BASE_URL",
        "freeplay-mcp"
      ],
      "env": {
        "FREEPLAY_API_KEY": "your-api-key",
        "FREEPLAY_BASE_URL": "https://app.freeplay.ai"
      }
    }
  }
}

Support

• Docs: https://docs.freeplay.ai
• Issues: https://github.com/freeplayai/freeplay-mcp/issues
• Security: security@freeplay.ai