registry/deploy
Repository files (latest commit first)
Filename Latest commit message Latest commit date
Preeti Dewani 9164415d59
Add failure modes telemetry (#646)
Telemetry to cover failure modes which are not covered by container logs
and metrics for finding resource constraints.

## Motivation and Context
When there is any issue with registry container we should be notified.

## How Has This Been Tested?
- Local seup

## Breaking Changes
- No

## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [X] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update

## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [ ] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [ ] My code follows the repository's style guidelines
- [ ] New and existing tests pass locally
- [ ] I have added appropriate error handling
- [ ] I have added or updated documentation as needed

## Additional context
- No additional exporter is used, taken advantage of opentelemetry
collector
- It covers metrics related to resource constraints, currently only
limited to default namespace.
- Takes cares of kubernetes events as logs which are the source of
figuring out any problem with service, covers all such scenarios where
pod is not able to start yet and get missed because there are no
container logs for such cases. Limited to default namespace.
- Taken care of daemonset deployment i.e. deploying otel collector as
agent by using correct filtering.
- Cardinality contributing factors are only pod ids (but have to observe
more), node ids will not increase cardinality as scale up will lead to
limited nodes.
- Shipping of metrics for resources happens every 60s and list of
metrics that will be emitted
[https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/receiver/kubeletstatsreceiver/metadata.yaml](url)

- Container errors

<img width="1440" height="816" alt="Screenshot 2025-10-10 at 1 21 14 AM"
src="https://github.com/user-attachments/assets/ba90a217-2a49-4522-aa44-a98c02adf95b"
/>




- Resource metrics

<img width="1440" height="816" alt="Screenshot 2025-10-10 at 1 23 51 AM"
src="https://github.com/user-attachments/assets/3467be96-db3c-4930-afa2-3cbf5f0ced8b"
/>
2025-10-20 11:57:49 -07:00
..
pkg Add failure modes telemetry (#646) 2025-10-20 11:57:49 -07:00
.gitignore deploy: Deploy the registry to GCP (#255) 2025-08-12 17:44:50 +01:00
go.mod Add monitoring infrastructure: victoriametrics and grafana (#328) 2025-09-02 12:40:43 +00:00
go.sum Add database backup functionality with GCS integration (#297) 2025-08-25 17:27:40 +01:00
main.go Add database backup functionality with GCS integration (#297) 2025-08-25 17:27:40 +01:00
Makefile infra: Improve local development flow and avoid false positive infra diffs (#267) 2025-08-15 12:13:51 +01:00
Pulumi.gcpProd.yaml Promote prod to 1.3.3 (#687) 2025-10-17 01:48:53 +03:00
Pulumi.gcpStaging.yaml Add monitoring infrastructure: victoriametrics and grafana (#328) 2025-09-02 12:40:43 +00:00
Pulumi.local.yaml Add monitoring infrastructure: victoriametrics and grafana (#328) 2025-09-02 12:40:43 +00:00
Pulumi.yaml feat(infra): Add Pulumi-based Kubernetes deployment infrastructure (#237) 2025-08-11 19:43:49 +01:00
README.md Fix the image reference for prod: from v1.3.0 to 1.3.0 (#669) 2025-10-14 19:33:19 +03:00

MCP Registry Kubernetes Deployment

This directory contains Pulumi infrastructure code to deploy the MCP Registry service to a Kubernetes cluster. It supports deploying the infrastructure locally (using an existing kubeconfig, e.g. with minikube) or to Google Cloud Platform (GCP).

Quick Start

Local Development

Pre-requisites:

  1. Ensure your kubeconfig is configured at the cluster you want to use. For minikube, run minikube start && minikube tunnel.
  2. Run make local-up to deploy the stack.
  3. Access the repository via the ingress load balancer. You can find its external IP with kubectl get svc ingress-nginx-controller -n ingress-nginx. Then run curl -H "Host: local.registry.modelcontextprotocol.io" -k https://<EXTERNAL-IP>/v0/ping to check that the service is up.

To change config

The stack is configured out of the box for local development. But if you want to make changes, run commands like:

PULUMI_CONFIG_PASSPHRASE="" pulumi config set mcp-registry:environment local
PULUMI_CONFIG_PASSPHRASE="" pulumi config set mcp-registry:githubClientSecret --secret <some-secret-value>

To delete the stack

make local-destroy and deleting the cluster (with minikube: minikube delete) will reset you back to a clean state.

Production Deployment (GCP)

Note: Deployments are automatically handled by GitHub Actions with separate workflows for staging and production:

  • Staging: All merges to the main branch automatically build and deploy the latest code to the staging environment via deploy-staging.yml. Staging always uses the :main Docker image tag.

  • Production: Deployment requires explicit configuration of the Docker image tag in Pulumi.gcpProd.yaml and is triggered automatically via deploy-production.yml when this config file is pushed to main. This GitOps-style approach provides manual control and an audit trail for production versions.

To deploy a specific version to production:

  1. Cut a release (if deploying a new version):

    # Via GitHub UI: https://github.com/modelcontextprotocol/registry/releases
    # Or via gh CLI:
    gh release create v1.2.3 --generate-notes
    

    This builds Docker images tagged as 1.2.3 and latest (note: image tags do not include the 'v' prefix)

  2. Update the production image tag in Pulumi.gcpProd.yaml:

    # Edit deploy/Pulumi.gcpProd.yaml
    # Change line: mcp-registry:imageTag: 1.2.3  (note: no 'v' prefix for Docker image tags)
    git add deploy/Pulumi.gcpProd.yaml
    git commit -m "Deploy version 1.2.3 to production"
    git push
    
  3. The production deployment workflow will automatically trigger and deploy the specified version

Manual Override: The steps below are preserved if a manual deployment override is needed.

Pre-requisites:

  • Pulumi CLI installed
  • A Google Cloud Platform (GCP) account
  • A GCP Service Account with appropriate permissions
  1. Create a project: gcloud projects create mcp-registry-prod
  2. Set the project: gcloud config set project mcp-registry-prod
  3. Enable required APIs: gcloud services enable storage.googleapis.com && gcloud services enable container.googleapis.com
  4. Create a service account with necessary permissions, and get the key:
    gcloud iam service-accounts create pulumi-svc
    sleep 10
    gcloud projects add-iam-policy-binding mcp-registry-prod --member="serviceAccount:pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com" --role="roles/container.admin"
    gcloud projects add-iam-policy-binding mcp-registry-prod --member="serviceAccount:pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com" --role="roles/compute.admin"
    gcloud projects add-iam-policy-binding mcp-registry-prod --member="serviceAccount:pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com" --role="roles/storage.admin"
    gcloud projects add-iam-policy-binding mcp-registry-prod --member="serviceAccount:pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com" --role="roles/storage.hmacKeyAdmin"
    gcloud iam service-accounts add-iam-policy-binding $(gcloud projects describe mcp-registry-prod --format="value(projectNumber)")-compute@developer.gserviceaccount.com --member="serviceAccount:pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com" --role="roles/iam.serviceAccountUser"
    gcloud iam service-accounts keys create sa-key.json --iam-account=pulumi-svc@mcp-registry-prod.iam.gserviceaccount.com
    
  5. Create a GCS bucket for Pulumi state: gsutil mb gs://mcp-registry-prod-pulumi-state
  6. Set Pulumi's backend to GCS: pulumi login gs://mcp-registry-prod-pulumi-state
  7. Get the passphrase file passphrase.prod.txt from the registry maintainers
  8. Init the GCP stack: PULUMI_CONFIG_PASSPHRASE_FILE=passphrase.prod.txt pulumi stack init gcpProd
  9. Set the GCP credentials in Pulumi config:
    # Base64 encode the service account key and set it
    pulumi config set --secret gcp:credentials "$(base64 < sa-key.json)"
    
  10. Deploy: make prod-up
  11. Access the repository via the ingress load balancer. You can find its external IP with: kubectl get svc ingress-nginx-controller -n ingress-nginx. Then run curl -H "Host: prod.registry.modelcontextprotocol.io" -k https://<EXTERNAL-IP>/v0/ping to check that the service is up.

Structure

├── main.go                 # Pulumi program entry point
├── Pulumi.yaml             # Project configuration
├── Pulumi.local.yaml       # Local stack configuration
├── Pulumi.gcpProd.yaml     # GCP production stack configuration
├── Pulumi.gcpStaging.yaml  # GCP staging stack configuration
├── Makefile                # Build and deployment targets
├── go.mod                  # Go module dependencies
├── go.sum                  # Go module checksums
└── pkg/                    # Infrastructure packages
    ├── k8s/                # Kubernetes deployment components
    │   ├── backup.go          # Database backup configuration
    │   ├── cert_manager.go    # SSL certificate management
    │   ├── deploy.go          # Deployment orchestration
    │   ├── ingress.go         # Ingress controller setup
    │   ├── monitoring.go      # Metrics and monitoring setup
    │   ├── postgres.go        # PostgreSQL database deployment
    │   └── registry.go        # MCP Registry deployment
    └── providers/          # Kubernetes cluster providers
        ├── types.go           # Provider interface definitions
        ├── gcp/               # Google Kubernetes Engine provider
        └── local/             # Local kubeconfig provider

Architecture Overview

Deployment Flow

  1. Pulumi program starts in main.go
  2. Configuration is loaded from Pulumi config files
  3. Provider factory creates appropriate cluster provider (GCP or local)
  4. Cluster provider sets up Kubernetes access
  5. k8s.DeployAll() orchestrates complete deployment:
    • Certificate manager for SSL/TLS
    • Ingress controller for external access
    • Database for data persistence
    • Backup infrastructure for database
    • Monitoring and metrics collection
    • MCP Registry application

Configuration

Parameter Description Required
environment Deployment environment (local/staging/prod) Yes
provider Kubernetes provider (local/gcp) No (default: local)
githubClientId GitHub OAuth Client ID Yes
githubClientSecret GitHub OAuth Client Secret Yes
imageTag Docker image tag for production environment Yes (prod only)
gcpProjectId GCP Project ID (required when provider=gcp) No
gcpRegion GCP Region (default: us-central1) No

Database Backups

The deployment uses K8up (a Kubernetes backup operator) that uses Restic under the hood.

When running locally they are stored in a Minio bucket. In staging and production, backups are stored in a GCS bucket.

Accessing Backup Files

Local Development (MinIO)

# Expose MinIO web console
kubectl port-forward -n minio svc/minio 9000:9000 9001:9001

Then open localhost:9001, login with username minioadmin and password minioadmin, and navigate to the k8up-backups bucket.

Staging and Production (GCS)

Decrypting and Restoring Backups

Backups are encrypted using Restic. To access the backup data:

  1. Download the backup files from the bucket:
    # Local (MinIO) - ensure port-forward is active: kubectl port-forward -n minio svc/minio 9000:9000 9001:9001
    AWS_ACCESS_KEY_ID=minioadmin AWS_SECRET_ACCESS_KEY=minioadmin \
      aws --endpoint-url http://localhost:9000 s3 sync s3://k8up-backups/ ./backup-files/
    
    # GCS (staging/production)
    gsutil -m cp -r gs://mcp-registry-{staging|prod}-backups/* ./backup-files/
    
  2. Install Restic
  3. Restore the backup:
    RESTIC_PASSWORD=password restic -r ./backup-files restore latest --target ./restored-files
    
    PostgreSQL data will be in ./restored-files/data/registry-pg-1/pgdata/

Troubleshooting

To configure kubectl to access an existing GKE cluster:

# Login
gcloud auth login
gcloud auth application-default login

# For production
gcloud container clusters get-credentials mcp-registry-prod --zone us-central1-b --project mcp-registry-prod

# For staging
gcloud container clusters get-credentials mcp-registry-staging --zone us-central1-b --project mcp-registry-staging

Check Status

kubectl get pods
kubectl get deployment
kubectl get svc
kubectl get ingress
kubectl get svc -n ingress-nginx

View Logs

kubectl logs -l app=mcp-registry
kubectl logs -l app=postgres

Check Backup Status

kubectl describe schedule.k8up.io 
kubectl get backup