Agent Toolkit

What's in the toolkit

mc-agent-toolkit plugin bundles all the skills, Monte Carlo MCP server, hooks, and editor-specific capabilities. Install once, get everything. When new features are added, they arrive automatically on the next plugin update.

Quick start

Prerequisites

• A Monte Carlo account with Editor role or above
• A supported AI coding agent (see Supported agents below)

Install the mc-agent-toolkit plugin

Claude Code (recommended — best support):

1. Add the marketplace:

   /plugin marketplace add monte-carlo-data/mc-agent-toolkit

2. Install the plugin:

   /plugin install mc-agent-toolkit@mc-marketplace

3. Authenticate — run /mcp, select the Monte Carlo server, and complete the OAuth flow in your browser.
4. Verify — ask Claude: "Test my Monte Carlo connection."

Cursor:

bash <(curl -fsSL https://raw.githubusercontent.com/monte-carlo-data/mc-agent-toolkit/main/plugins/cursor/scripts/install.sh)

Then restart Cursor. The Monte Carlo MCP server will prompt for OAuth on first use.

GitHub Copilot CLI:

git clone https://github.com/monte-carlo-data/mc-agent-toolkit.git

# Install hooks into your dbt project
./mc-agent-toolkit/plugins/copilot/scripts/install.sh /path/to/your/dbt-project

# Install the plugin (skills + MCP)
copilot plugin install ./mc-agent-toolkit/plugins/copilot

For other agents (OpenCode, Codex), see the plugins page on GitHub.

Using skills standalone (without the plugin)

If your editor isn't listed above or you prefer to install skills individually:

1. Configure the Monte Carlo MCP server:

   claude mcp add --transport http monte-carlo-mcp https://integrations.getmontecarlo.com/mcp

2. Install a skill:
   Bash

   npx skills add monte-carlo-data/mc-agent-toolkit --skill prevent

3. Authenticate via /mcp and complete the OAuth flow.

See the MCP server docs for advanced configuration options.

Supported agents

The mc-agent-toolkit plugin is available for multiple AI coding agents:

Editor compatibility: VS Code users can use Copilot CLI or Claude Code. JetBrains users can use Copilot CLI. Cursor is a standalone editor. Claude Code, Copilot CLI, and OpenCode also run in any terminal.

How MC Prevent works

MC Prevent is the flagship feature of the toolkit. When installed via the plugin, it uses hooks to enforce a safety-first workflow:

1. You edit a dbt model — the pre-edit hook blocks until a change impact assessment runs. The agent surfaces downstream blast radius, active alerts, monitor coverage, and a risk-tiered recommendation.
2. You confirm and edit — the post-edit hook records the change. The skill offers to generate monitors-as-code for new logic.
3. You commit — the pre-commit hook checks for unresolved monitor coverage gaps.
4. You validate — run /mc-validate or ask the agent to generate validation queries. Targeted SQL checks are saved to validation/<table>_<timestamp>.sql.

Without the plugin, the skill still works — it just relies on the agent following instructions rather than hooks enforcing the workflow.

How Monitor Creation works

Monitor Creation guides agents through a validate-then-create workflow that prevents the common failure modes of AI-generated monitors (invalid fields, nonexistent tables, wrong parameters).

1. Table validation -- the agent confirms the target table exists in Monte Carlo.
2. Field verification -- the agent checks that referenced field names and types are valid for the chosen monitor type.
3. Monitor generation -- the agent builds the monitor with correct parameters and outputs monitors-as-code YAML.

Supported monitor types: metric, validation, comparison, custom SQL, and table monitors.

If you have the mc-agent-toolkit plugin installed, the skill is already available -- just ask your agent to create a monitor.

Resources

• GitHub repository — source code, detailed READMEs, and architecture docs
• Contributing — guidelines for adding skills and plugins
• MCP Server docs — Monte Carlo MCP server configuration and auth options