add-tools

name	add-tools
description	Add tools to your agent and grant required permissions in databricks.yml. Use when: (1) Adding MCP servers, Genie spaces, vector search, or UC functions to agent, (2) Permission errors at runtime, (3) User says 'add tool', 'connect to', 'grant permission', (4) Configuring databricks.yml resources.

Add Tools & Grant Permissions

Profile reminder: All databricks CLI commands must include the profile from .env: databricks <command> --profile <profile>

Don't have the resource yet? See create-tools skill first.

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:

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:

resources:
  apps:
    agent_openai_advanced:
      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
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
lakebase-autoscaling.yaml	Lakebase autoscaling postgres	Agent memory storage (autoscaling)
experiment.yaml	MLflow experiment	Tracing (already configured)
app.yaml	Databricks App (app-to-app)	Custom MCP servers hosted as Apps
custom-mcp-server.md	Custom MCP apps	Apps starting with mcp-*

Custom MCP Servers (Databricks Apps)

Declare the target app as an app resource in databricks.yml — the bundle grants CAN_USE on deploy. Requires Databricks CLI v0.298.0+.

resources:
  apps:
    agent_openai_advanced:
      resources:
        - name: 'mcp_server'
          app:
            name: 'mcp-my-server'
            permission: CAN_USE

See examples/custom-mcp-server.md for the full flow (agent code + YAML + deploy).

MCP Error Handling

MCP tool calls can fail (network issues, permission errors, timeouts). The OpenAI Agents SDK catches tool errors by default and returns the error message to the LLM. To customize timeout behavior for MCP servers:

mcp_server = McpServer(
    url=f"{host}/api/2.0/mcp/genie/{space_id}",
    name="genie",
    timeout=60.0,  # Increase timeout for slow tools like Genie (default: 20s)
)

For local function tools, see create-tools skill > examples/local-python-tools.md for failure_error_function patterns.

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