databricks Discover Available Tools
Run tool discovery BEFORE writing agent code to understand what resources are available in the workspace.
Run Discovery
npm run discover-tools
Options:
# Limit to specific catalog/schema
npm run discover-tools -- --catalog my_catalog --schema my_schema
# Output as JSON
npm run discover-tools -- --format json --output tools.json
# Save markdown report
npm run discover-tools -- --output tools.md
# Use specific Databricks profile
npm run discover-tools -- --profile DEFAULT
What Gets Discovered
| Resource Type | Description | MCP URL Pattern |
|---|---|---|
| UC Functions | SQL UDFs as agent tools | {host}/api/2.0/mcp/functions/{catalog}/{schema} |
| UC Tables | Structured data for querying | (via UC functions) |
| Vector Search Indexes | RAG applications | {host}/api/2.0/mcp/vector-search/{catalog}/{schema} |
| Genie Spaces | Natural language data interface | {host}/api/2.0/mcp/genie/{space_id} |
| Custom MCP Servers | Apps starting with mcp-* |
{app_url}/mcp |
| External MCP Servers | Via UC connections | {host}/api/2.0/mcp/external/{connection_name} |
Using Discovered Tools in Code
After discovering tools, add them to your agent in src/mcp-servers.ts:
import { DatabricksMCPServer } from "@databricks/langchainjs";
export function getMCPServers(): DatabricksMCPServer[] {
return [
// Example: Add a Genie space
DatabricksMCPServer.fromGenieSpace("01f1037ebc531bbdb27b875271b31bf4"),
// Example: Add Databricks SQL
new DatabricksMCPServer({
name: "dbsql",
path: "/api/2.0/mcp/sql",
}),
// Example: Add UC functions from a schema
DatabricksMCPServer.fromUCFunction("my_catalog", "my_schema"),
// Example: Add vector search
DatabricksMCPServer.fromVectorSearch(
"my_catalog",
"my_schema",
"my_index"
),
];
}
Next Steps
After adding MCP servers to your agent:
- Grant permissions in
databricks.yml(see add-tools skill) - Test locally with
npm run dev(see run-locally skill) - Deploy with
databricks bundle deploy(see deploy skill)