Sold by: Code Creator
Deployed on AWS
Free Trial
AWS Free Tier
Deploy a private MCP control center on AWS with automated HTTPS setup, scoped client tokens, and controlled AI tool access for your team.
Overview
AI Tool Private Control Center with MCP - A Private AWS Foundation for Governed AI Tool Access
Code Creator's AI Tool Private Control Center with MCP gives technical teams a private, controlled AWS foundation for connecting AI applications to approved tools through a single governed HTTPS MCP endpoint deployed entirely within your own AWS account.
The Problem: Scattered, Ungoverned AI Tool Connections
As teams adopt AI assistants, agents, and automation workflows, tool connections multiply without centralized oversight. Each application establishes its own one-off integration, creating fragmented access patterns with no consistent control point, no scoped permissions, and no repeatable operational foundation.
The Solution: One Private MCP Control Point in Your AWS Account
Move from scattered AI tool connections to a single controlled HTTPS MCP endpoint running in your infrastructure. Register compatible MCP tool servers once, then connect approved AI assistants, agents, workflows, developer tools, and custom applications through a consistent private control layer.
Scoped Client Access Controls - Create separate client tokens for each AI application and restrict every token to only the MCP tools that application is authorized to use. This delivers clearer separation between clients, controlled permissions, and a repeatable governance model for AI tool access.
Automated First-Boot Provisioning - The server is built on Ubuntu 26.04 with Docker Compose and automated first-boot setup. At launch, the system creates buyer-specific runtime configuration, a trusted HTTPS endpoint, administrator configuration, and a restricted starter token -- no manual server setup, HTTPS configuration, or access control scaffolding required.
Operational Readiness Validation - The included safe readiness tool confirms that the endpoint is working before you connect additional compatible MCP tools. A browser status page confirms server readiness, while the private MCP endpoint requires a valid client token for all tool interactions.
Secure Administration via SSH - Administration is performed through secure SSH helper commands. Tool results appear in the connected AI client, agent, workflow, or custom application where your users already work.
Who This Product Is For
This control center is designed for platform engineering, DevOps, and development teams that need to introduce AI tool access with governance from day one. Whether you are connecting AI coding assistants to internal developer tools, enabling AI agents to interact with approved automation endpoints, or building custom AI applications that require controlled access to registered MCP tool servers, this product provides the private infrastructure layer so you do not have to build it from scratch.
What You Get
- A private HTTPS MCP endpoint running entirely in your AWS account
- Automated first-boot provisioning with buyer-specific runtime configuration
- Scoped client token management to control which tools each AI application can access
- Docker Compose-based architecture on Ubuntu 26.04
- SSH helper commands for secure server administration
- Browser-accessible status page for readiness confirmation
- Readiness validation tooling to verify endpoint operation before connecting tools
- AWS Marketplace-ready AMI engineering by Code Creator
What This Product Is Not
This server is a private control layer for MCP tools. It is not an AI model host, chatbot, or prebuilt collection of third-party business tools. It provides the governed connection infrastructure between your AI applications and the MCP tool servers you register and approve.
Get Started
Launch the AMI in your AWS account, let the automated first-boot process configure your private MCP endpoint, verify readiness, and begin registering your MCP tool servers and issuing scoped client tokens. For questions about deployment planning or to discuss your specific use case, reach out to Code Creator through the support contact provided in this listing.
Code Creator charges apply for the private MCP control layer, automated first-boot provisioning, buyer-specific runtime configuration, trusted HTTPS endpoint creation, scoped client access controls, readiness validation, operational helper commands, and AWS Marketplace-ready AMI engineering.
Highlights
- Private AWS MCP Control Center - Replace scattered AI tool connections with a single private HTTPS MCP endpoint running inside your own AWS account. Your MCP traffic stays within your infrastructure, giving you full network-level control over how AI applications reach approved tools. The trusted HTTPS configuration is handled automatically during first boot, so your endpoint is production-ready without manual TLS setup.
- Scoped Client Tokens and Tool Access - Assign every AI application its own authentication token and restrict which MCP tools each client can access. This separation ensures that one application cannot reach tools approved only for another, reducing your blast radius and giving administrators fine-grained control over AI tool permissions across teams and workloads.
- Automated First-Boot Provisioning and Readiness Validation - Launch the AMI and let the automated first-boot process handle runtime configuration, trusted HTTPS endpoint creation, administrator setup, and starter token generation. Built-in readiness testing confirms your MCP endpoint is operational, and SSH-based helper tooling provides ongoing commands for token management, tool registration, and operational tasks.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t3.medium Recommended | $0.04 |
t3.micro | $0.04 |
t2.2xlarge | $0.04 |
t3.large | $0.04 |
t3.2xlarge | $0.04 |
t3.small | $0.04 |
t3.xlarge | $0.04 |
t3.nano | $0.04 |
Dimensions summary
You pay by the hour based on the EC2 instance size you run. The eight options are all instance types, not feature tiers. Each provides the same pre-built application; they differ only in compute capacity. The t3.nano, t3.micro, t3.small, and t3.medium suit lighter workloads. The t3.large, t3.xlarge, t3.2xlarge, and t2.2xlarge offer more compute for heavier use. Your cost scales with the size you choose and the hours you run it. You can switch instance sizes to match your needs, since billing is usage-based.
Top-of-mind questions for buyers
Each dimension bills per hour that the matching EC2 instance runs. One unit equals one instance-hour of that specific type. The instance type sets your compute capacity, such as CPU and memory. Larger types like t3.2xlarge provide more compute; smaller ones like t3.nano provide less.
Software charges apply per hour while the instance runs. A fully stopped instance stops accruing hourly software charges. You may still pay underlying AWS storage fees for attached volumes, but the software meters running time only. Restarting the instance resumes hourly billing.
You pay only for the hours each instance runs, with no upfront commitment. Billing meters actual instance-hours. This suits variable or short-lived workloads, since you can start, stop, and switch instance types to match your needs and cost.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Version 1.2 delivers a private AWS MCP control center with automated first boot setup, trusted HTTPS, separate client tokens, restricted starter access, a safe readiness test, SSH helper commands, and clean AMI preparation.
Additional details
Resources
Vendor resources
Support
Vendor support
This is the primary channel for questions about deployment, configuration, troubleshooting, and general product assistance. Please include your AWS account details and a description of the issue when reaching out to help expedite resolution. info@codecreator.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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