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MCP Servers and agent skills

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Agent skills

Materialize provides the following open-source agent skills to help developers build with Materialize.

Skill What it provides When to use
mcp-developer-analysis Exact catalog schemas, diagnostic workflows, remediation runbooks, and guardrails for known pitfalls (cluster-scoped queries, uint8 ID mismatches, etc.). Operational introspection and troubleshooting via the materialize-developer server. Examples: “why is my materialized view stale?”, “what can I optimize to save costs?”, “is my source healthy?”
materialize-docs Comprehensive Materialize documentation, including SQL syntax, idiomatic patterns, data ingestion, concepts, and best practices (400+ reference files). Authoring view definitions, learning concepts, looking up patterns. Useful with either MCP server. Examples: “show me how to deduplicate a stream”, “what’s the idiomatic top-K pattern?”, “how do I create a Kafka source?”
materialize-dbt dbt-materialize adapter usage: materializations, profile configuration, index creation, blue/green deployments, and testing. Managing Materialize pipelines with dbt. Examples: “write a dbt model for a materialized view”, “how do I do a blue/green deployment with dbt?”
materialize-terraform-provider Provider configuration for Cloud and self-managed, navigation into the provider’s auto-generated resource reference, cross-resource patterns, import workflows, and gotchas. Managing Materialize resources declaratively with Terraform. Examples: “create a Kafka source with Terraform”, “import my existing clusters into Terraform state”, “set up RBAC grants in Terraform”
materialize-terraform-self-managed Module layout and variables for deploying self-managed Materialize on AWS, Azure, and GCP: networking, Kubernetes, backend URL formats, instance sizing, upgrades, and gotchas. Deploying or operating self-managed Materialize infrastructure with Terraform. Examples: “deploy Materialize on EKS”, “what instance types should Materialize nodes use?”, “upgrade my self-managed Materialize”

MCP servers

Materialize provides built-in Model Context Protocol (MCP) servers that AI agents can use. The MCP interface is served directly by the database; no sidecar process or external server is required. These endpoints use JSON-RPC 2.0 over HTTP POST (default port 6876) and support the MCP initialize, tools/list, and tools/call methods.

Endpoint Path Description
Agent /api/mcp/agent Discover and query your real-time data products over HTTP.
For details, see MCP Server for agents.
Available starting in v26.24
Developer /api/mcp/developer Read mz_* system catalog tables for troubleshooting and observability.
For details, see MCP Server for developer.

See also

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