CloudNativePG MCP Server

An MCP server for managing PostgreSQL clusters through the CloudNativePG operator.

This version uses the MCP Base scaffold for its server layout, authentication, container build, Helm chart, prompt registry, and test harness. The previous manual implementation is retained under deprecated-v1/ for reference.

Tool Surface

The server exposes the CloudNativePG tools from the v1 implementation:

• list_postgres_clusters

• get_cluster_status

• create_postgres_cluster

• scale_postgres_cluster

• delete_postgres_cluster

• list_postgres_roles

• create_postgres_role

• update_postgres_role

• delete_postgres_role

• list_postgres_databases

• get_postgres_database_status

• create_postgres_database

• delete_postgres_database

create_postgres_database supports CloudNativePG Database CRD create-time locale options, including encoding, locale, locale_provider, locale_collate, locale_ctype, icu_locale, icu_rules, builtin_locale, and collation_version. get_postgres_database_status reports the current Database CRD spec values for those options along with the operator reconciliation status.

It also includes MCP Base scaffold admin tools for prompt management:

• admin_reload_prompts

• admin_get_prompt_manifest

Related MCP server: PostgreSQL MCP Server

Layout

• src/cnpg_mcp_server.py: production FastMCP HTTP entrypoint

• src/cnpg_mcp_test_server.py: no-auth/OIDC test entrypoint

• src/cnpg_mcp_tools.py: CloudNativePG tool implementations and registration

• src/mcp_context.py: MCP context wrapper with user identity extraction

• src/auth_*.py: MCP Base scaffold authentication support

• chart/: Helm deployment assets

• test/: MCP plugin test harness

• SCAFFOLD_INVENTORY.md: MCP Base scaffold artifact hashes

Development

Create an environment and install dependencies:

python -m venv .venv
. .venv/bin/activate
pip install -r requirements.txt -r test/requirements.txt

Run the scaffold registration smoke test:

python bin/smoke_test.py

Run the local no-auth MCP test suite:

python test/run-local-tests.py

Run the CloudNativePG Kubernetes integration tests adapted from deprecated-v1/test/plugins:

python test/run-local-tests.py --include-integration
# or
make test-integration

These tests create, scale, update, and delete real CloudNativePG resources. Useful optional settings:

• CNPG_MCP_TEST_NAMESPACE: namespace for test resources

• CNPG_MCP_TEST_CLUSTER_PREFIX: generated cluster name prefix

• CNPG_MCP_TEST_STORAGE_SIZE: per-instance storage size, default 1Gi

• CNPG_MCP_TEST_CREATE_WAIT_SECONDS: cluster readiness timeout, default 300

• CNPG_MCP_TEST_SCALE_WAIT_SECONDS: scale readiness timeout, default 300

Running Locally

The scaffold entrypoint uses HTTP transport:

python src/cnpg_mcp_server.py --host 0.0.0.0 --port 4200

The test server can be run without authentication:

python src/cnpg_mcp_test_server.py --host 127.0.0.1 --port 4201 --no-auth

Kubernetes Access

The tools use the Kubernetes Python client. They load configuration in this order:

1. In-cluster service account configuration

2. Local kubeconfig from ~/.kube/config or KUBECONFIG

Most tools accept an optional namespace. When omitted, the current Kubernetes context namespace is used, falling back to default.

For in-cluster Helm deployments, the server uses the deployment service account. By default the chart grants that service account CNPG and secret permissions only in the Helm release namespace. To manage CNPG resources in another namespace, pass the tool's namespace argument and grant the service account access there:

rbac:
  targetNamespaces:
    - application-databases

For a shared MCP deployment that must operate in arbitrary namespaces, opt in to cluster-wide RBAC:

rbac:
  clusterWide: true

Cluster-wide mode grants secret access across namespaces, so prefer explicit targetNamespaces when the target set is known.

Deployment

The MCP Base scaffold includes Docker and Helm assets:

make build
make push
make helm-install

Use python bin/configure-make.py to generate make.env for image and namespace settings before using the deployment targets.