spark-connect-mcp

MCP server exposing Apache Spark Connect (and Databricks Connect) via DataFrame and SQL tools for AI agents.

Install

Choose one backend — do not install both.

# OSS Spark Connect
pip install "spark-connect-mcp[spark]"

# Databricks Connect
pip install "spark-connect-mcp[databricks]"

Quick Start

Add to your Claude Code MCP config:

{
  "mcpServers": {
    "spark": {
      "command": "uvx",
      "args": ["--from", "spark-connect-mcp[databricks]", "spark-connect-mcp"]
    }
  }
}

For OSS Spark Connect, replace [databricks] with [spark].

Configuration

All connection config is set via environment variables — the MCP tools require no parameters to start a session.

OSS Spark Connect

Set SPARK_REMOTE to your Spark Connect server URL (PySpark's native env var):

export SPARK_REMOTE=sc://localhost:15002

Databricks Connect

Optionally set DATABRICKS_CONFIG_PROFILE to select a profile from ~/.databrickscfg (defaults to DEFAULT):

export DATABRICKS_CONFIG_PROFILE=my-workspace

Serverless compute is used by default inside Databricks Apps, Jobs, and notebooks — no env var needed.

Preflight Size Checks

Before executing an action tool (show, collect, count, describe, save, save_as_table), spark-connect-mcp runs a lightweight preflight check that inspects the Spark Catalyst optimized plan statistics to estimate result size without triggering a Spark job. If the estimate exceeds configurable thresholds the tool returns a warning instead of executing.

Prerequisites — making statistics available

Preflight relies on Catalyst Cost-Based Optimization (CBO) statistics. How you populate them depends on your environment:

Confidence tiers

The quality of the estimate depends on what statistics are present in the plan:

Threshold configuration

Set via environment variables (defaults shown):

# Maximum estimated bytes before warning (default 1 GB)
export SPARK_CONNECT_MCP_PREFLIGHT_MAX_BYTES=1073741824

# Maximum estimated rows before warning (default 10 million)
export SPARK_CONNECT_MCP_PREFLIGHT_MAX_ROWS=10000000

# Disable preflight entirely
export SPARK_CONNECT_MCP_PREFLIGHT_ENABLED=false

Per-session overrides

Use the set_preflight_threshold tool to adjust thresholds for a single session without changing env vars:

{
  "tool": "set_preflight_threshold",
  "arguments": {
    "session_id": "abc123",
    "max_bytes": 5368709120,
    "max_rows": 50000000
  }
}

Pass "enabled": false to disable preflight for that session.

The force escape hatch

Every action tool accepts a force parameter. Pass force=True to skip the preflight check entirely and execute immediately:

{
  "tool": "collect",
  "arguments": { "df_id": "df-001", "limit": 100, "force": true }
}

SQL Tool

The sql tool executes a SQL query against an active Spark session. By default it enforces read-only SQL — only SELECT, WITH...SELECT, SHOW, DESCRIBE, and EXPLAIN statements are permitted. Write operations (INSERT, UPDATE, DELETE, DROP, CREATE, ALTER, MERGE, TRUNCATE, COPY INTO, OPTIMIZE, VACUUM, etc.) are rejected before reaching Spark.

Multi-statement SQL (e.g. SELECT 1; DROP TABLE foo) is also blocked — submit one statement at a time.

Malformed SQL that cannot be parsed is rejected fail-closed — the query is never executed.

Allowing write SQL

To permit write operations, set the escape-hatch environment variable:

export SPARK_CONNECT_MCP_ALLOW_WRITE_SQL=true

This bypasses all read-only enforcement. Intended for trusted environments where the agent needs DDL or DML access.

Status

Under active development. See issues for the roadmap.

License

Apache-2.0