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Flightcontrol MCP. Manage every AWS resource change through conversation.

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Flightcontrol (AWS PaaS Deployments) MCP on Cursor AI Code Editor MCP Client Flightcontrol (AWS PaaS Deployments) MCP on Claude Desktop App MCP Integration Flightcontrol (AWS PaaS Deployments) MCP on OpenAI Agents SDK MCP Compatible Flightcontrol (AWS PaaS Deployments) MCP on Visual Studio Code MCP Extension Client Flightcontrol (AWS PaaS Deployments) MCP on GitHub Copilot AI Agent MCP Integration Flightcontrol (AWS PaaS Deployments) MCP on Google Gemini AI MCP Integration Flightcontrol (AWS PaaS Deployments) MCP on Lovable AI Development MCP Client Flightcontrol (AWS PaaS Deployments) MCP on Mistral AI Agents MCP Compatible Flightcontrol (AWS PaaS Deployments) MCP on Amazon AWS Bedrock MCP Support

Just plug in your AI agents and start using Vinkius.

Flightcontrol (AWS PaaS Deployments) MCP Server manages and automates AWS infrastructure directly from your AI client. Use it to list projects, create new environments, update service scaling, and manage VPCs without leaving your IDE.

Trigger deployments, check status, and manage full service lifecycles using natural conversation.

What your AI agents can do

Create aws account connection

Establishes a new AWS account connection for the project.

Create cloudfront invalidation

Invalidates the CloudFront cache for a specified domain.

Create deployment

Triggers a new deployment based on filters from a Git repository.

+ 21 more capabilities included
Manage Project Structure

List all existing projects or automate the setup of a new project, including integrating a Git repository.

Configure Service Environments

Create, edit, or manage environment settings—like standard or preview environments—for any service within a project.

Control Service Scaling

Retrieve current service scaling information and manually adjust the number of service instances needed.

Run Deployments and Swaps

Trigger a full deployment from a Git repository and perform controlled traffic swaps between Blue and Green environments.

Audit AWS Connections

Check AWS account details and manage VPC configurations to ensure all required infrastructure is connected and compliant.

Supported MCP Clients

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients
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AI Agent

Flightcontrol MCP Server: 24 Tools for AWS PaaS Management

Use these tools to manage every step of your cloud deployment pipeline, from creating projects to swapping live traffic.

create019e5d1a

create aws account connection

Establishes a new AWS account connection for the project.

create019e5d1a

create cloudfront invalidation

Invalidates the CloudFront cache for a specified domain.

create019e5d1a

create deployment

Triggers a new deployment based on filters from a Git repository.

create019e5d1a

create domain group

Creates a group to manage multiple domain certificates.

create019e5d1a

create environment

Provisions a new, isolated environment within a project.

create019e5d1a

create environment variables

Creates and sets environment variables for a specific service or environment.

create019e5d1a

create job execution

Starts a one-off background job in a scheduler service.

create019e5d1a

create project

Automates the setup and creation of a new project.

create019e5d1a

create service variables

Sets up variable definitions for a service.

edit019e5d1a

edit environment

Modifies the settings of an existing service environment.

edit019e5d1a

edit preview environment

Changes the settings of a project's preview environment.

get019e5d1a

get aws account details

Retrieves the current details of the AWS account connection.

get019e5d1a

get cloudfront invalidation status

Checks the status of a CloudFront cache invalidation request.

get019e5d1a

get deployment status

Checks the current status and logs of a running deployment.

get019e5d1a

get domain details

Retrieves detailed information for a single domain name.

get019e5d1a

get domains from group

Lists all domains contained within a specific certificate group.

get019e5d1a

get job execution status

Checks the status and output of a scheduled background job.

get019e5d1a

get service

Fetches specific operational details for a named service.

get019e5d1a

get service scaling

Retrieves the current instance count and scaling configuration for a service.

list019e5d1a

list projects

Lists all projects currently managed by the team.

list019e5d1a

list services

Gets a paginated list of all available services.

swap019e5d1a

swap blue green

Swaps traffic between the Blue and Green environments for a service.

trigger019e5d1a

trigger deploy hook

Initiates a deployment using a secret URL hook.

update019e5d1a

update service scaling

Manually adjusts the number of running instances for a service.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

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Start with Flightcontrol (AWS PaaS Deployments), then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 4,700+ others, all in one place
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  • Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector

Flightcontrol (AWS PaaS Deployments) MCP Server manages your AWS infrastructure directly from your AI client. You'll use this server to list projects, create new environments, update service scaling, and manage VPCs without ever touching the AWS console. You can trigger deployments, check status, and manage the full service lifecycle just by talking to your agent.

Manage Project Structure

  • You can list all projects using list_projects. You'll also automate the setup of a new project, including connecting a Git repository, by calling create_project.
  • You manage service environments by using create_environment to provision a new, isolated workspace, or by calling edit_environment to modify an existing service environment. You can also change settings for a project's preview environment using edit_preview_environment.

Service Operation

  • You get specific operational details for a service using get_service. You can also check the current instance count and scaling setup with get_service_scaling.
  • You manually adjust the number of running service instances using update_service_scaling. You'll also set up variable definitions for a service with create_service_variables, or create and set environment variables for a specific service or environment via create_environment_variables.
  • You can get a paginated list of all available services using list_services.

Deployment and Traffic Control

  • You trigger a full deployment from a Git repository by calling create_deployment, or initiate a deployment using a secret URL hook via trigger_deploy_hook.
  • You monitor the status and logs of any running deployment with get_deployment_status.
  • You perform controlled traffic swaps between the Blue and Green environments for a service using swap_blue_green.

Infrastructure and Networking

  • You establish a new AWS account connection for your project using create_aws_account_connection, and you can retrieve the current AWS account details with get_aws_account_details.
  • You manage domain certificates by using create_domain_group to create a group for multiple domain names, and you can list all domains in that group with get_domains_from_group. You'll also get detailed info for a single domain with get_domain_details.
  • You can run a one-off background job in a scheduler service using create_job_execution, and check its status and output with get_job_execution_status.
  • You can also create a group to manage multiple domain certificates, and you'll use create_domain_group and get_domains_from_group for this.

How Flightcontrol MCP Works

  1. 1 Subscribe to the server and provide your Flightcontrol API Key.
  2. 2 Your AI client connects to the server, authorizing access to your AWS account.
  3. 3 You issue a natural language command (e.g., 'Deploy the latest commit to staging for project X'). The agent executes the necessary tools to complete the task.

The bottom line is, you manage all your AWS PaaS deployments from a single conversation, never needing to switch tools or log into the AWS console.

Who Is Flightcontrol MCP For?

The DevOps engineer who gets tired of clicking through AWS dashboards at 2 AM. The full-stack developer who needs to test staging environments while coding. Infrastructure Leads who must audit complex project configurations quickly. If your job involves managing microservices across multiple AWS environments, this saves hours of manual CLI work.

DevOps Engineer

Uses get_deployment_status to check deployment progress and create_service_variables to update config without writing a script.

Full-stack Developer

Uses create_environment to spin up a new preview environment for testing, and then edit_preview_environment to tweak settings before committing.

Infrastructure Lead

Uses list_projects to audit the entire portfolio, and get_aws_account_details to verify core connections.

What Changes When You Connect

  • Manage project structure by listing all projects with list_projects or automating a new one with create_project. You never lose track of where a service lives.
  • Control service scaling immediately. Instead of digging into dashboards, use get_service_scaling to check current instances, then update_service_scaling to scale up or down.
  • Guarantee zero downtime releases using swap_blue_green. It handles the traffic shift, giving you a safe, controlled way to go live.
  • Audit AWS connections and VPCs quickly. Use get_aws_account_details and list_projects to verify project compliance without manual checks.
  • Maintain environment parity. You can create_environment and then edit_environment to ensure staging always matches production config.
  • Track deployments end-to-end. Use create_deployment to start a release, and get_deployment_status to track it until completion.

Real-World Use Cases

01

Need to check if the latest release worked?

The QA team finishes testing and needs to verify the deployment status. They tell their agent: 'What's the status for project X?' The agent uses get_deployment_status and reports back the final state. If it fails, the team uses get_service to see which specific service failed and why, solving the issue instantly.

02

A feature needs to go live, but we can't risk downtime.

The product manager approves the release. The engineer asks the agent to run the release: 'Swap the traffic for the main API to Green.' The agent executes swap_blue_green and confirms the controlled rollout, minimizing risk and zeroing downtime.

03

The staging environment variables are out of date.

A developer notices a config drift. They tell the agent to fix it: 'Set the API key variable in the staging environment.' The agent uses create_environment_variables and edit_environment to update the configuration instantly, ensuring parity with production.

04

We need to test a service before the full project is ready.

An engineer only needs to test a component. They ask the agent to create a temporary workspace: 'Create a new preview environment for service Y.' The agent runs create_environment and edit_preview_environment, giving the developer a safe sandbox to work in.

The Tradeoffs

Manual AWS Console Navigation

Logging into the AWS console, navigating to the service, finding the environment, and clicking 'Deploy' multiple times. This takes 15 minutes and requires jumping between 5 different tabs.

Tell your agent: 'Deploy the latest commit to staging for project X.' The agent handles the entire sequence using create_deployment, and you just monitor the progress with get_deployment_status.

Running scripts with stale variables

Writing a complex bash script that assumes environment variables are set, but the variables were never updated in the cloud console, causing the deployment to fail hours later.

First, use get_service_scaling to confirm the service is ready. Then, use create_environment_variables to update the required settings before running create_deployment.

Ignoring domain dependencies

Trying to set up a new domain name for a service without first creating the domain group, leading to certificate errors and deployment failure.

First, run create_domain_group to establish the certificate group. Then, use get_domain_details to ensure the new domain is correctly registered before any other deployment tools run.

When It Fits, When It Doesn't

Use this server if your team manages microservices, needs to deploy across multiple environments (dev, staging, prod), or relies heavily on AWS PaaS features. You need a single source of truth for the entire deployment lifecycle.

Don't use this if you only manage simple, non-AWS services, or if your infrastructure changes are purely manual (e.g., physical hardware). If you just need to check a single resource, some tools might suffice, but the full suite is better. Use a simple scripting language if you only need to list projects (list_projects). But if you need to change anything—scaling, variables, environments—you need this full toolset.

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flightcontrol. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This server provides 24 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Available Capabilities

create_aws_account_connection create_cloudfront_invalidation create_deployment create_domain_group create_environment create_environment_variables create_job_execution create_project create_service_variables edit_environment edit_preview_environment get_aws_account_details get_cloudfront_invalidation_status get_deployment_status get_domain_details get_domains_from_group get_job_execution_status get_service get_service_scaling list_projects list_services swap_blue_green trigger_deploy_hook update_service_scaling

Managing complex cloud deployments shouldn't mean opening 10 different tabs.

Today, updating a service requires a painful manual dance. You log into the AWS dashboard, find the service, check the current environment settings, and copy-paste environment variables into a separate console. If you miss a single click or copy the wrong variable, the deployment fails, and you waste an hour debugging the console.

With this MCP server, you just talk to your agent. You tell it exactly what you want—'Deploy the new feature to staging.' The agent executes the necessary `create_environment_variables`, `create_deployment`, and checks the status, all without you touching the dashboard. It just works.

Flightcontrol MCP Server: Zero-Touch Service Control

Manual deployments involve checking scaling limits, manually swapping traffic, and running multiple scripts. Now, you tell your agent to swap the environment: 'Swap the main API to Green.' The agent runs `swap_blue_green` and manages the complex traffic shift. You get reliable, controlled rollouts, period.

This isn't just a faster way to click buttons. It gives you transactional control over your entire service lifecycle, guaranteeing that the state you *want* is the state you *get*.

Common Questions About Flightcontrol MCP

How do I use the create_deployment tool? +

You trigger a deployment by naming the tool and providing the necessary repository filters. The agent handles the actual deployment process and gives you a job ID to track it.

What is the difference between create_environment and edit_environment? +

Use create_environment when you need a brand new environment (e.g., 'staging'). Use edit_environment when the environment already exists, and you just need to change its settings.

Can I check the status of a deployment using get_deployment_status? +

Yes, get_deployment_status is designed for this. You give it the deployment ID, and it reports the current status and any logs immediately.

How does swap_blue_green work? +

The swap_blue_green tool performs a controlled traffic shift. It swaps the active environment from Blue to Green (or vice versa), ensuring zero downtime during the switch.

Do I need to run create_aws_account_connection first? +

Yes, you must establish the connection first. create_aws_account_connection links the server to your AWS account, which is the prerequisite for all other infrastructure management tools.

How do I use get_service_scaling to change my service's capacity? +

You use get_service_scaling to read the current scaling configuration. Then, use update_service_scaling to manually adjust the instances. This lets you manage capacity directly through your agent.

What is the difference between list_projects and get_aws_account_details? +

list_projects retrieves a list of all projects owned by your team. get_aws_account_details provides specific, high-level details about the connected AWS account itself, regardless of the project.

Do I need to use create_job_execution for scheduled tasks? +

No, create_job_execution triggers a one-off job in a scheduler service. For persistent, scheduled tasks, you'll need to configure a dedicated scheduling resource outside of this server.

Can I see all my active projects and their IDs? +

Yes! Use the list_projects tool to retrieve a complete list of projects owned by your team, including their unique identifiers and repository links.

How do I check the configuration of a specific service? +

Simply provide the Service ID to the get_service tool. Your agent will fetch the full details, including type, status, and current environment mapping.

Is it possible to scale my services using the AI? +

Yes, the update_service_scaling tool allows you to manually adjust the scaling parameters of your services directly through the conversation.

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Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
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JetBrains JetBrains
Vercel Vercel
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