How do I install the bricks and context mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

What credentials does it need?

It reads `MCP_AUTH_PATH`, `MCP_CONFIG_PATH` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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Bricks And Context MCP Server

Think of it as a bridge: your AI asks questions, this server translates them into Databricks API calls, and returns structured, AI-friendly responses.

Local serverstdioPython

What is the Bricks And Context MCP Server?

Think of it as a bridge: your AI asks questions, this server translates them into Databricks API calls, and returns structured, AI-friendly responses.

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

Tool	What it does
execute_sql_query	Run SQL with bounded, AI-safe output
discover_schemas	List all schemas in the workspace
discover_tables	List tables in a schema with metadata
describe_table	Get column types, nullability, structure
get_table_sample	Preview rows for data exploration
connection_health	Verify Databricks connectivity
list_jobs	List jobs with optional name filtering
get_job_details	Full job config: schedule, cluster, tasks
get_job_runs	Run history with state and duration
trigger_job	Start a job with optional parameters
cancel_job_run	Stop a running job
get_job_run_output	Retrieve logs, errors, notebook output
cache_stats	Hit rates, memory usage, category breakdown
performance_stats	Operation latencies, error rates, health

How to install the Bricks And Context MCP Server

{
  "mcpServers": {
    "databricks": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/bricks-and-context",
        "run",
        "python",
        "run_mcp_server.py"
      ],
      "env": {
        "MCP_AUTH_PATH": "/path/to/bricks-and-context/auth.yaml",
        "MCP_CONFIG_PATH": "/path/to/bricks-and-context/config.json"
      }
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

Variable	Description	Required
MCP_AUTH_PATH	Declared in the maintainer’s client configuration.	Check documentation
MCP_CONFIG_PATH	Declared in the maintainer’s client configuration.	Check documentation

Example prompts to try

“Use Bricks And Context to execute sql query.”
“Use Bricks And Context to discover schemas.”
“Use Bricks And Context to discover tables.”

Frequently asked questions

Think of it as a bridge: your AI asks questions, this server translates them into Databricks API calls, and returns structured, AI-friendly responses. Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.