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methodify

local-spark-mcp

by methodify
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOCAL_SPARK_JAVA_HOMENoPath to Java 17 home directory (overrides runtime.java_home in config)
LOCAL_SPARK_WORKSPACE_NAMENoName of the Fabric workspace to connect to (optional, defaults to local-only)

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
run_codeA

Run a cell of Python/PySpark against the persistent session. State persists across calls; spark, sc, F, T, Window are pre-imported. Returns captured stdout and the last-expression echo, or the traceback if the cell raised.

run_sqlA

Run a Spark SQL statement and return rows as a text table. Reference Fabric tables by name (lakehouse.table) — they auto-mount on first use and stay available for the session. limit caps returned rows (default from config, ~100) and the result flags truncation.

session_infoA

Show the live Spark session: version, master, current database, the catalog databases, and any Fabric lakehouses registered this session.

reset_runtimeA

Reset the runtime: restart the Spark session and wipe all state — variables, imports, and mounted tables. Use to start from a clean slate.

list_lakehousesA

List the Fabric lakehouses available in this session. Each is registered as a Spark database; its tables are mounted on demand.

list_tablesA

List the Delta tables in a Fabric lakehouse. Tables are not queryable via SQL until you mount them with mount_table or mount_lakehouse.

mount_tableA

Explicitly register one Fabric Delta table as <lakehouse>.<table>. Usually unnecessary — run_sql auto-mounts referenced tables — but useful to pre-register a table for use in run_code.

mount_lakehouseA

Mount ALL tables in a lakehouse as <lakehouse>.<table>. Convenient, but can register many tables at once.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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