sceptre-mcp-server

sceptre-mcp-server

MCP server that exposes Sceptre CloudFormation management operations as tools for AI agents.

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README

sceptre-mcp-server

A Model Context Protocol (MCP) server that exposes Sceptre CloudFormation management operations as tools for AI agents.

What it does

AI agents (Claude, Kiro, etc.) can connect to this server and manage AWS CloudFormation stacks through Sceptre's Python API. The server exposes 22 tools covering the full stack lifecycle:

  • Stack lifecycle — create, update, delete, launch
  • Querying — status, describe, outputs, resources, events
  • Templates — generate, validate
  • Diff & drift — diff against deployed state, detect and show drift
  • Change sets — create, describe, list, execute, delete
  • Discovery — list stacks, dump resolved config

Requirements

  • Python 3.10+
  • A configured Sceptre project with config/ and templates/ directories

Installation

pip install sceptre-mcp-server

Or run directly without installing:

uvx sceptre-mcp-server

MCP Client Configuration

Kiro

Add to .kiro/settings/mcp.json:

{
  "mcpServers": {
    "sceptre": {
      "command": "uvx",
      "args": ["sceptre-mcp-server"],
      "env": {
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "sceptre": {
      "command": "uvx",
      "args": ["sceptre-mcp-server"]
    }
  }
}

Tools Reference

Every tool requires a sceptre_project_dir parameter pointing to your Sceptre project root. Stack-specific tools also require a stack_path relative to the config/ directory.

Stack Lifecycle

Tool Parameters Description
create_stack sceptre_project_dir, stack_path Create a new CloudFormation stack
update_stack sceptre_project_dir, stack_path Update an existing stack
delete_stack sceptre_project_dir, stack_path Delete a stack
launch_stack sceptre_project_dir, stack_path Create or update a stack as needed

Querying

Tool Parameters Description
get_stack_status sceptre_project_dir, stack_path Get current stack status
describe_stack sceptre_project_dir, stack_path Get full stack details
describe_stack_outputs sceptre_project_dir, stack_path Get stack output values
describe_stack_resources sceptre_project_dir, stack_path List stack resources
describe_stack_events sceptre_project_dir, stack_path Get stack event history

Templates

Tool Parameters Description
generate_template sceptre_project_dir, stack_path Render the CloudFormation template
validate_template sceptre_project_dir, stack_path Validate template with CloudFormation

Diff & Drift

Tool Parameters Description
diff_stack sceptre_project_dir, stack_path, diff_type Diff local template vs deployed (deepdiff or difflib)
drift_detect sceptre_project_dir, stack_path Detect configuration drift
drift_show sceptre_project_dir, stack_path, drifted_only Show drift details

Change Sets

Tool Parameters Description
create_change_set sceptre_project_dir, stack_path, change_set_name Create a change set
describe_change_set sceptre_project_dir, stack_path, change_set_name Describe a change set
list_change_sets sceptre_project_dir, stack_path List all change sets
execute_change_set sceptre_project_dir, stack_path, change_set_name Execute a change set
delete_change_set sceptre_project_dir, stack_path, change_set_name Delete a change set

Discovery & Configuration

Tool Parameters Description
list_stacks sceptre_project_dir, stack_path (optional) List stacks in the project
dump_config sceptre_project_dir, stack_path Dump resolved stack configuration

Example Usage

Once connected, an AI agent can invoke tools like:

> List all stacks in my project at /home/user/infra

Calls: list_stacks(sceptre_project_dir="/home/user/infra")

> What's the status of the dev VPC stack?

Calls: get_stack_status(sceptre_project_dir="/home/user/infra", stack_path="dev/vpc.yaml")

> Show me what would change if I deploy the prod API stack

Calls: diff_stack(sceptre_project_dir="/home/user/infra", stack_path="prod/api.yaml")

AWS Configuration

Sceptre uses the standard AWS credential chain. To specify a profile or region, pass environment variables through your MCP client config:

{
  "mcpServers": {
    "sceptre": {
      "command": "uvx",
      "args": ["sceptre-mcp-server"],
      "env": {
        "AWS_PROFILE": "my-profile",
        "AWS_DEFAULT_REGION": "us-west-2"
      }
    }
  }
}

Contributing

See CONTRIBUTING.md for development setup, testing, pre-commit hooks, and type checking.

License

Apache-2.0

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