How do I install the Add Tools skill?

Run npx skillmds@latest add databricks/add-tools-9 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Add Tools safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Add Tools?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Add Tools free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Add Tools?

databricks (@databricks) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Add Tools by databricks — Agent Skill

Name: Add Tools
Author: databricks

Add Tools

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.

databricks 628afad 11 files · 7.7 KB Updated Sep 17, 2026

File contents

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_agents_sdk_multiagent:
      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_agents_sdk_multiagent:
      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

---name: add-tools-9description: 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`:```pythonfrom databricks_openai.agents import McpServergenie_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`:```yamlresources: apps: agent_openai_agents_sdk_multiagent: 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 ExamplesSee 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+**.```yamlresources: apps: agent_openai_agents_sdk_multiagent: 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 HandlingMCP 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:```pythonmcp_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`

Frequently asked questions