Connect Model Monster MCP

In 10–15 minutes, you will create or securely reuse a Model Monster API key, connect your coding agent through the Model Context Protocol (MCP), and verify access to the intended organization and team with two read-only discovery calls. You will finish with the exact destination values needed to begin system work. The verification stops at discovery, so it does not list, create, scan, import, or change a system.

Before you begin

You will need:

• A Model Monster account
• An MCP-capable coding agent
• Access to at least one existing Model Monster organization and team

An organization and team identify where you are working in Model Monster. Each has a slug: the exact machine-readable value that you supply to MCP tools. Later calls receive the organization and team slugs explicitly, so keep both values available after you find them.

If an organization and team have already been chosen for this work, use that pair. Otherwise, choose an existing pair you are authorized to access. The steps are the same either way.

The client configuration establishes the connection, but it does not choose a destination. You will prove the connection first, then use the values returned by Model Monster to identify where the next workflow should operate.

If your client already has a working model-monster server, continue to Verify the connection and choose an organization.

Create or reuse an API key

Your API key gives the MCP client your authorized Model Monster access. It does not extend that access beyond the key owner's effective permissions. Reuse a current key only if you already have its full raw value stored securely; the prefix shown in API Keys is not enough to configure a client. If you have the full value, continue to Load the API key into your environment. Otherwise, create a new key. Using a separate key for each client or environment makes the credential easier to manage and revoke later.

To create a key:

1. Sign in to Model Monster and open the organization's Settings.
2. Select API Keys, then select Create API Key.
3. In Create New API Key, enter a descriptive API Key Name *.
4. If you already know the tutorial destination, select Restricted, open Restricted Team, and use Select a team to choose the intended team. This is the least-privilege option for access to that team.

1. Create the key. When its full value appears, copy it immediately and store it in your normal secret-management workflow. You will not be able to view the full key again.

Load the API key into your environment

In the terminal environment that you will use to launch your MCP client, set the key:

export MM_API_KEY="<YOUR_MODEL_MONSTER_API_KEY>"

Every client configuration in this tutorial reads the value from MM_API_KEY, keeping the raw secret out of the configuration itself. Launch the client from the same environment. The variable belongs to that environment and is not automatically added to a client that is already open. If the client is running, restart it after setting the variable so the new process receives it.

If you use a local .env workflow, keep that file uncommitted and load it before launching the client.

Add Model Monster to your MCP client

Choose your client below and add a server named model-monster. Every option uses the hosted URL https://api.modelmonster.ai/api/v1/mcp/ and reads the Bearer token from MM_API_KEY.

Keep the trailing slash in the URL.

Apply only the configuration for the client you use. After saving it, restart or reload the client as needed, then confirm that model-monster is registered before moving to the shared discovery steps.

Claude Code

Add this configuration to the project's .mcp.json or a supported user configuration location:

{
  "mcpServers": {
    "model-monster": {
      "type": "http",
      "url": "https://api.modelmonster.ai/api/v1/mcp/",
      "headers": {
        "Authorization": "Bearer ${MM_API_KEY}"
      }
    }
  }
}

Launch Claude Code from the environment where MM_API_KEY is loaded. Claude Code may ask you to approve a project-scoped server.

Codex

Register the server from the command line:

codex mcp add model-monster --url https://api.modelmonster.ai/api/v1/mcp/ --bearer-token-env-var MM_API_KEY

Alternatively, add the equivalent entry to ~/.codex/config.toml:

[mcp_servers.model-monster]
url = "https://api.modelmonster.ai/api/v1/mcp/"
bearer_token_env_var = "MM_API_KEY"

Run codex mcp list to confirm that the server is registered without exposing the key.

VS Code with GitHub Copilot Agent Mode

Add this configuration to the project's .vscode/mcp.json:

{
  "servers": {
    "model-monster": {
      "type": "http",
      "url": "https://api.modelmonster.ai/api/v1/mcp/",
      "headers": {
        "Authorization": "Bearer ${env:MM_API_KEY}"
      }
    }
  }
}

Cursor

Add this configuration to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "model-monster": {
      "type": "http",
      "url": "https://api.modelmonster.ai/api/v1/mcp/",
      "headers": {
        "Authorization": "Bearer ${env:MM_API_KEY}"
      }
    }
  }
}

Verify the connection and choose an organization

Ask your coding agent:

Use the model-monster MCP server and call list_orgs.
Show me the organization names and slugs you can access.

A successful result returns the names and slugs of organizations available to your key. If list_orgs returns organizations, the Model Monster MCP connection is working.

Review the returned names to find your destination. If an organization has already been chosen for this work, find it in the returned list. Otherwise, choose an accessible existing organization where you intend to work.

Copy that organization's returned slug and retain it as <ORG_SLUG>. The name helps you recognize the organization; the slug is the value later tools accept.

A successful result with an empty organization list still proves that the configured server and authenticated call worked, but it does not provide a usable destination. Obtain access to an organization, then repeat the same read-only call before continuing.

Find a team and record the destination

Replace <ORG_SLUG> with the exact organization slug you retained, then ask your coding agent:

Call list_teams for organization <ORG_SLUG>.
Show me the team names and slugs you can access.

A successful result returns the names and slugs of teams available within that organization.

Review the team names and returned slugs. If a team has already been chosen for this work, confirm that it appears under the expected organization. Otherwise, choose an existing team you are authorized to access and intend to use in the next workflow.

If the successful result contains no teams, the read still confirms that the organization-scoped call worked. It cannot complete the destination, however, because the next workflow needs both values. Obtain access to a team in that organization, then repeat list_teams for the same organization.

Ask the agent to repeat the exact organization and team pair. Record the returned values in your tutorial notes rather than relying on conversation history:

Organization slug: <ORG_SLUG>
Team slug: <TEAM_SLUG>

You now have the organization and team you will use for later work. Keep both slugs together as a pair for the next workflow.

Continue to system scanning

The model-monster server has responded to both read-only calls, and you have retained an accessible organization and team slug pair.

Continue with AI-Assisted Blueprint Modeling, bringing <ORG_SLUG> and <TEAM_SLUG> with you. It explains how to prepare evidence, work with your agent, and validate the resulting System Blueprint.