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Glama
RadiumGu

AWS FIS MCP Server

by RadiumGu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
AWS_REGIONNoThe AWS region to use for FIS operations
AWS_PROFILENoThe AWS profile to use for authentication

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
list_experiment_templatesB
List all AWS FIS experiment templates in the specified region.

Args:
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing experiment templates information
get_experiment_templateB
Get detailed information about a specific AWS FIS experiment template.

Args:
    template_id: ID of the experiment template to retrieve
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing detailed template information
list_experimentsB
List all AWS FIS experiments in the specified region.

Args:
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing experiments information
get_experimentB
Get detailed information about a specific AWS FIS experiment.

Args:
    experiment_id: ID of the experiment to retrieve
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing detailed experiment information
start_experimentA
Start a new AWS FIS experiment based on an experiment template.

Args:
    template_id: ID of the experiment template to use
    region: AWS region to use (default: us-east-1)
    client_token: Optional client token for idempotency
    
Returns:
    JSON string containing the started experiment information
stop_experimentB
Stop a running AWS FIS experiment.

Args:
    experiment_id: ID of the experiment to stop
    region: AWS region to use (default: us-east-1)
    
Returns:
    JSON string containing the stopped experiment information
create_experiment_templateB
Create a new AWS FIS experiment template.

Args:
    name: Name for the experiment template
    description: Description of the experiment template
    targets: Dictionary of targets configuration
    actions: Dictionary of actions configuration
    role_arn: ARN of the IAM role to use for the experiment
    stop_conditions: List of stop conditions
    region: AWS region to use (default: us-east-1)
    
Returns:
    JSON string containing the created template information
delete_experiment_templateB
Delete an AWS FIS experiment template.

Args:
    template_id: ID of the experiment template to delete
    region: AWS region to use (default: us-east-1)
    
Returns:
    Success or error message
list_action_typesB
List all available AWS FIS action types.

Args:
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing action types information
generate_template_exampleB
Generate an example AWS FIS experiment template for a given target and action type.

Args:
    target_type: Target resource type (default: aws:ec2:instance)
    action_type: Action type to perform (default: aws:ec2:stop-instances)
    region: AWS region to use (default: us-east-1)
    
Returns:
    JSON string containing an example template configuration

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored across 10 tools

Disambiguation5/5

Every tool has a clearly distinct purpose targeting specific AWS FIS operations with no overlap. Tools like create_experiment_template, delete_experiment_template, and get_experiment_template handle different lifecycle stages of templates, while start_experiment and stop_experiment manage experiment execution separately. The list_* tools provide distinct listing functions for different resource types.

Naming Consistency5/5

All tools follow a consistent verb_noun naming pattern with snake_case throughout. The naming convention is perfectly predictable: create_experiment_template, delete_experiment_template, get_experiment, list_experiments, start_experiment, stop_experiment, etc. This consistency makes the tool set immediately understandable and navigable.

Tool Count5/5

With 10 tools, this server is well-scoped for AWS FIS operations. Each tool earns its place by covering essential CRUD operations for experiment templates (create, delete, get, list), experiment management (start, stop, get, list), plus supporting utilities like list_action_types and generate_template_example. This provides comprehensive coverage without being overwhelming.

Completeness5/5

The tool set provides complete lifecycle coverage for AWS FIS operations. It includes full CRUD for experiment templates (create, get, list, delete), experiment execution (start, stop, get, list), plus discovery tools (list_action_types) and a helpful utility (generate_template_example). There are no obvious gaps - agents can create templates, run experiments, monitor them, and clean up resources as needed.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources