Add Tools & Grant Permissions

Name: add-tools
Rating: 92
Author: databricks

After adding any MCP server to your agent, you MUST grant the app access in databricks.yml.

Without this, you'll get permission errors when the agent tries to use the resource.

Workflow

Step 1: Add MCP server in agent_server/agent.py:

python

from databricks_openai.agents import McpServer

genie_server = McpServer(
    url=f"{host}/api/2.0/mcp/genie/01234567-89ab-cdef",
    name="my genie space",
)

agent = Agent(
    name="my agent",
    model="databricks-claude-3-7-sonnet",
    mcp_servers=[genie_server],
)

Step 2: Grant access in databricks.yml:

yaml

resources:
  apps:
    agent_openai_agents_sdk:
      resources:
        - name: 'my_genie_space'
          genie_space:
            name: 'My Genie Space'
            space_id: '01234567-89ab-cdef'
            permission: 'CAN_RUN'

Step 3: Deploy with databricks bundle deploy (see deploy skill)

Resource Type Examples

See the examples/ directory for complete YAML snippets:

File	Resource Type	When to Use
`uc-function.yaml`	Unity Catalog function	UC functions via MCP
`uc-connection.yaml`	UC connection	External MCP servers
`vector-search.yaml`	Vector search index	RAG applications
`sql-warehouse.yaml`	SQL warehouse	SQL execution
`serving-endpoint.yaml`	Model serving endpoint	Model inference
`genie-space.yaml`	Genie space	Natural language data
`experiment.yaml`	MLflow experiment	Tracing (already configured)
`custom-mcp-server.md`	Custom MCP apps	Apps starting with `mcp-*`

Custom MCP Servers (Databricks Apps)

Apps are not yet supported as resource dependencies in databricks.yml. Manual permission grant required:

Step 1: Get your agent app's service principal:

bash

databricks apps get <your-agent-app-name> --output json | jq -r '.service_principal_name'

Step 2: Grant permission on the MCP server app:

bash

databricks apps update-permissions <mcp-server-app-name> \
  --service-principal <agent-app-service-principal> \
  --permission-level CAN_USE

See examples/custom-mcp-server.md for detailed steps.

Important Notes

•MLflow experiment: Already configured in template, no action needed
•Multiple resources: Add multiple entries under resources: list
•Permission types vary: Each resource type has specific permission values
•Deploy after changes: Run databricks bundle deploy after modifying databricks.yml