knowledge_base: add mcp_and_model_services example

knowledge_base/mcp_and_model_services/.gitignore

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+.databricks

knowledge_base/mcp_and_model_services/README.md

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+# MCP and model services
+
+This Declarative Automation Bundles example defines an AI Gateway model service, a model provider service, and an MCP service in a Unity Catalog schema.
+The model service routes chat requests to a Databricks foundation model. The model provider service connects to Anthropic with relayed authentication. The MCP service exposes the tools of an external MCP server.
+
+For more information, see the [bundle resources documentation](https://docs.databricks.com/aws/en/dev-tools/bundles/resources#model_services).
+
+## Prerequisites
+
+* Databricks CLI v1.20.0 or above, authenticated with OAuth (`databricks auth login`)
+* `jq`
+* A Unity Catalog catalog where you can create schemas
+* A schema-level HTTP connection to an MCP server. See [Register an external MCP server](https://docs.databricks.com/aws/en/ai-gateway/register-mcp-service).
+
+## Usage
+
+1. Select a pay-per-token foundation model from the `system.ai` schema, for example `system.ai.databricks-claude-sonnet-4-6`.
+
+2. Deploy the bundle. Replace the placeholders with your catalog, model, and connection:
+   ```bash
+   databricks bundle deploy --var catalog=<catalog> --var chat_model=<model> --var mcp_connection=<connection>
+   ```
+
+3. Send a chat request to the model service. The schema name is `<catalog>.dev_<your_user>_ai_services`:
+   ```bash
+   databricks api post /ai-gateway/mlflow/v1/chat/completions --json '{
+     "model": "<catalog>.dev_<your_user>_ai_services.chat",
+     "messages": [{"role": "user", "content": "What is Databricks?"}]
+   }'
+   ```
+
+4. List the tools of the MCP service. The command gets the host and a token from the CLI:
+   ```bash
+   curl -X POST "$(databricks auth describe --output json | jq -r .details.host)/ai-gateway/mcp-services/<catalog>.dev_<your_user>_ai_services.docs" \
+     -H "Authorization: Bearer $(databricks auth token | jq -r .access_token)" \
+     -H "Accept: application/json, text/event-stream" \
+     -H "Content-Type: application/json" \
+     -d '{"jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {}}'
+   ```
+
+5. Remove the services and the schema:
+   ```bash
+   databricks bundle destroy --var catalog=<catalog> --var chat_model=<model> --var mcp_connection=<connection>
+   ```

knowledge_base/mcp_and_model_services/databricks.yml

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+bundle:
+  name: mcp_and_model_services
+  # AI Gateway services can only be deployed with the direct deployment engine.
+  engine: direct
+
+include:
+  - resources/*.yml
+
+variables:
+  catalog:
+    description: Existing Unity Catalog catalog for the services schema.
+  chat_model:
+    # Example: system.ai.databricks-claude-sonnet-4-6
+    description: Pay-per-token foundation model in system.ai, as catalog.schema.model.
+  mcp_connection:
+    description: Schema-level HTTP connection to an MCP server, as catalog.schema.connection.
+
+targets:
+  dev:
+    mode: development
+    default: true
+    workspace:
+      root_path: /Workspace/bundle-examples/${bundle.name}/dev/${workspace.current_user.short_name}

knowledge_base/mcp_and_model_services/resources/ai_services.schema.yml

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+resources:
+  schemas:
+    ai_services:
+      catalog_name: ${var.catalog}
+      name: ai_services

knowledge_base/mcp_and_model_services/resources/anthropic.model_provider_service.yml

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+resources:
+  model_provider_services:
+    anthropic:
+      parent: schemas/${resources.schemas.ai_services.id}
+      model_provider_service_id: anthropic
+      comment: Anthropic provider with relayed authentication.
+      config:
+        provider_type: EXTERNAL_MODEL_PROVIDER_TYPE_ANTHROPIC
+        allow_all_targets: true
+        anthropic:
+          # Each request supplies its own Anthropic credential. No key is stored.
+          relayed: {}

knowledge_base/mcp_and_model_services/resources/chat.model_service.yml

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+resources:
+  model_services:
+    chat:
+      parent: schemas/${resources.schemas.ai_services.id}
+      model_service_id: chat
+      comment: Routes chat requests to a Databricks foundation model.
+      config:
+        routing:
+          destinations:
+            - name: primary
+              destination_type: DESTINATION_TYPE_PAY_PER_TOKEN_FOUNDATION_MODEL
+              pay_per_token_config:
+                model: models/${var.chat_model}

knowledge_base/mcp_and_model_services/resources/docs.mcp_service.yml

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+resources:
+  mcp_services:
+    docs:
+      parent: schemas/${resources.schemas.ai_services.id}
+      mcp_service_id: docs
+      comment: Exposes the tools of an external MCP server.
+      config:
+        source_connection:
+          # The connection holds the MCP server URL and credentials.
+          name: connections/${var.mcp_connection}