Comparison

MCP Orchestrator vs AWS Bedrock AgentCore

Both products run MCP servers. They are not the same product. AgentCore is a managed runtime for the MCP servers AWS hosts. Magertron's MCP Orchestrator is a Kubernetes-native governance plane for the MCP servers across your enterprise, wherever they run.

Last updated May 2026 · Curtis Mager, founder of Magertron
MCP Orchestrator

The Kubernetes-native MCP control plane

Self-hosted in your cluster. Deploys MCP servers as pods, routes through Envoy with JWT authentication, and is being built to federate inventory and governance across managed, self-managed, and shadow MCP servers in your environment.

  • Runs in your Kubernetes cluster — any cloud, on-prem, air-gapped
  • OSS Free up to 20 servers, no signup, no credit card
  • Your data and credentials never leave your network
  • Fixed-capacity pricing, predictable at any scale
AWS Bedrock AgentCore

Managed runtime substrate for AI agents

A serverless AWS platform for hosting agents and MCP servers in per-session microVMs. Twelve modular components — Runtime, Gateway, Memory, Identity, Browser, Code Interpreter, Observability, and more — billed independently on consumption.

  • Fully managed by AWS, available in fourteen regions
  • Per-session microVM isolation, up to 8-hour sessions
  • Native integration with Bedrock models and the AWS ecosystem
  • Consumption-based pricing, idle wait time not charged
The framing

Hosting MCP servers and governing MCP servers are different problems.

When AgentCore launched in October 2025, the obvious question for anyone building MCP infrastructure was: is this the end of the category? It is a serious product from a serious company. AWS shipped microVM-per-session isolation, up to 8-hour session limits, consumption-based pricing that does not charge for I/O wait, and a Gateway service that centralizes MCP tool routing across MCP servers, REST APIs, and AWS Lambda functions. It is good work.

It is also not the answer to the enterprise MCP problem, because AgentCore solves hosting, and the enterprise problem is governance.

A managed runtime inventories what its customers register with it. In a 5,000-person enterprise, the small minority of MCP servers that platform engineering built deliberately — with security review, with intent to be managed — belong on AgentCore (if the customer is already on AWS). The other ninety percent — built by application teams, by data engineers, by individual developers wrapping internal REST APIs in 30 minutes — were never registered with anyone. They are running on dev VMs, under desks, in development namespaces, on employee laptops. They have credentials. They are not, and will never be, configured as AgentCore Gateway targets, because the people who run them do not know AgentCore Gateway exists.

That is not a critique of AWS. It is a recognition that managed hosting and federated governance are different layers of the stack. AgentCore is built for the first. MCP Orchestrator is being built for the second.

Side by side
MCP Orchestrator AWS AgentCore
Deployment model Self-hosted on Kubernetes (any cloud, on-prem, air-gapped) AWS-managed PaaS, 14 regions
Where MCP servers run Kubernetes pods in your cluster microVMs in AWS infrastructure
Cloud lock-in None Runs anywhere k8s runs AWS-native Tightly coupled to Bedrock and AWS services
Pricing model Software licensing. OSS Free up to 20 servers. Tiered pricing above. Fixed capacity. Consumption-based per service. Runtime at $0.0895/vCPU-hr + $0.00945/GB-hr. Twelve components billed independently.
Predictable at scale Yes Cost scales with cluster capacity, not request volume Conditional Favorable at low/moderate volume; crossover point exists for high-traffic workloads
Data sovereignty Full Servers, credentials, and traffic stay in your network Regional Data resides in selected AWS regions, subject to AWS compliance posture
Air-gapped deployment Supported Not applicable AgentCore is a managed cloud service
Time to first MCP server Hours. Install k3s, deploy Helm chart, register server. Minutes. Push a container, deploy.
Session isolation Pod-level isolation, namespace policy microVM per session Strong tenant isolation
Session length limit No fixed limit — runs as long as the pod runs Up to 8 hours per session
Auto-scale to zero Not built-in HPA scales replicas, minimums are configurable Yes Native to AgentCore Runtime
Auth and identity Bring your own OAuth/OIDC provider. JWT validation at the Envoy data plane. AgentCore Identity (Cognito or external OAuth). Federated identity for tool targets.
MCP discovery and inventory Roadmap Federation across config files, endpoint inspection, egress logs, and source repos Out of scope AgentCore manages what customers register; does not discover shadow MCP
Observability Standard Kubernetes telemetry: Prometheus, OpenTelemetry, your existing stack AgentCore Observability via CloudWatch, OpenTelemetry exports, Datadog/Dynatrace integrations
Memory, code interpreter, browser as services Out of scope Included Managed Memory, Code Interpreter, Browser services
Multi-cloud or hybrid Yes Same control plane across AWS, GCP, Azure, on-prem AWS only
Maturity Pre-1.0, active development by a small team GA since October 2025, mature core with new features still shipping
Vendor Magertron (independent startup) Amazon Web Services

So which one should you pick?

Pick MCP Orchestrator when

Sovereignty, control, or federation matters more than time-to-deploy.

  • Regulated industries where data cannot leave your network — defense, financial services with localization mandates, regulated healthcare with PHI residency requirements, EU-strict deployments.
  • Multi-cloud or non-AWS environments — Azure-first, GCP-first, or primarily on-premises operations.
  • Existing Kubernetes investment with platform tooling already in place — Prometheus, ArgoCD, OPA, service mesh.
  • Shadow MCP discovery — when the MCP servers you most need to govern are the ones nobody registered with anyone.
  • Predictable economics at scale — fixed cluster capacity vs. per-session metering.
  • Air-gapped or sovereign-cloud deployments — where managed cloud services are categorically excluded.
Pick AgentCore when

You're already on AWS and just want to ship agents fast.

  • AWS-committed organization with existing Bedrock workloads, IAM posture, and operational tooling in AWS.
  • Need Memory, Code Interpreter, or Browser as managed services — capabilities MCP Orchestrator does not provide.
  • Bursty, low-to-moderate volume where consumption pricing is cheaper than fixed compute.
  • Time-to-first-agent is the critical constraint — AgentCore is a container away from running; MCP Orchestrator requires k8s setup.
  • You want AWS to operate the substrate — patches, scaling, isolation, and observability handled by Amazon.
The honest take

These are complementary products, not adversaries.

The mature enterprise MCP posture twelve months from now will not be MCP Orchestrator or AgentCore. It will be MCP Orchestrator and AgentCore, plus other runtimes, plus discovery sources across endpoint inspection and egress proxies and source repositories. AgentCore hosts the MCP servers that belong on AWS. MCP Orchestrator runs the ones that belong in your cluster. The federation layer above both does inventory, policy, and governance across the entire estate.

"We use AgentCore" is not an MCP governance strategy. "We govern every MCP server in our environment — including the ones on AWS, on-prem, and on employee laptops" is the beginning of one.

See where MCP Orchestrator fits in your stack.

Talk through your environment, your existing infrastructure, and where MCP governance fits. Or grab the Helm chart and try it yourself.

Schedule a Demo View on GitHub