How do I connect MCP Apache Spark History Server MCP Server to Claude?

Run `claude mcp add mcp-apache-spark-history-server -- uvx --from mcp-apache-spark-history-server spark-mcp` in Claude Code, or add the same command and arguments under mcpServers in Cursor's mcp.json or Claude Desktop's claude_desktop_config.json, then restart the client. The blocks above are ready to paste.

Is MCP Apache Spark History Server MCP Server free?

The listed licence is Apache-2.0. Check the upstream terms for permitted use and commercial requirements; a public repository does not by itself mean the software is free or open source. Connected APIs and hosted services may have separate charges.

What can MCP Apache Spark History Server MCP Server do?

MCP Apache Spark History Server MCP Server documents 19 tools to the agent, including aws_analyze_spark_workload, aws_spark_code_recommendation, compare_job_environments. The descriptions above come from project documentation. A live handshake does not test individual tool behavior.

MCP Apache Spark History Server

Unclaimed

by kubeflow

MCP Server and CLI for Apache Spark History Server. Debug Spark applications from AI agents, scripts, or the terminal.

Set up this server

Compare servers My Stack

01 / Choose your client

02 / Before you connect

Authentication is not specified. Check the project instructions before connecting.

Install the runtime required by the project and make it available to your client.

Project instructionsEnvironment variable names (optional)

Use names from the project instructions, separated by commas. Enter names only, never secret values.

03 / Add the configuration

Source: generated from public install instructions

claude mcp add --transport stdio 'mcp-apache-spark-history-server' -- 'uvx' '--from' 'mcp-apache-spark-history-server' 'spark-mcp'

Run in your terminal after replacing any placeholders.

04 / Check it in your client

Open your client’s MCP settings and confirm the server connects and lists its tools. A copied configuration does not confirm a working connection.

apache-sparkbig-datadata-processingkubernetesmcpmcp-server

Is this your MCP server?

This listing was auto-indexed from the public record. Claim it to edit the page, set compatibility and unlock growth tools. Takes under two minutes.

Claim this server

Security profile

Claimed and verified servers get a weekly static scan that shows what the code can reach: external services, environment variables, shell commands, agent configuration folders, plus any dependencies with known advisories. Claim this listing to get one. How the security profile works

19 of 19 tools

Documented tools (19)

From project documentation. A server handshake does not verify each tool’s description or behavior.

aws_analyze_spark_workload

One-shot root cause analysis of failed/slow Spark workloads

aws_spark_code_recommendation

Code fix recommendations for identified Spark issues

compare_job_environments

Diff Spark configs between two applications

compare_job_performance

Diff performance metrics between two applications

compare_sql_executions

Compare aggregated performance metrics (stages, tasks, shuffle, spill, GC) between two SQL executions; opt-in plan-structure diff

compare_stages

Compare two stages (optionally across applications): stage metrics and per-task p25/p50/p75/max quantiles

get_environment

Spark config, JVM info, system properties, classpath; optional section filter to return a single part

get_executor_summary

Aggregate metrics across all executors

get_executor_thread_dump

JVM thread dump for a driver/executor, with state/name/blocked filters (running apps only)

get_job_bottlenecks

Identify bottlenecks across stages, tasks, and executors

get_resource_usage_timeline

Chronological executor add/remove with resource totals

get_sql_execution

SQL execution header by default; opt-in plan, node metrics, job summaries, aggregated stage metrics, and stage list

get_stage

Stage detail with attempt and task metric distributions

list_applications

List applications with optional status, date, and limit filters; pass appid for a single application's detail (status, resources, duration, attempts). Returned applications always include their attempts.

list_executors

List executors with executor-id filtering and sorting (failed-tasks/duration/gc/id)

list_jobs

List jobs with status/job-id filtering and sorting (e.g. slowest by duration)

list_sql_executions

List SQL executions as curated summaries, with status/description filters, sorting, and a default limit

list_stage_task_failures

Failed tasks of a stage with their error messages (exception/stack trace)

list_stages

List stages with status filtering and sorting (e.g. slowest by duration)

Tool change history

Compared across complete checks of the same configuration. Tools were listed, not invoked. Input-schema changes are not measured here.

No complete tool checks yet.

FAQ

Questions about MCP Apache Spark History Server MCP Server

How do I connect MCP Apache Spark History Server MCP Server to Claude?: Run `claude mcp add mcp-apache-spark-history-server -- uvx --from mcp-apache-spark-history-server spark-mcp` in Claude Code, or add the same command and arguments under mcpServers in Cursor's mcp.json or Claude Desktop's claude_desktop_config.json, then restart the client. The blocks above are ready to paste.
Is MCP Apache Spark History Server MCP Server free?: The listed licence is Apache-2.0. Check the upstream terms for permitted use and commercial requirements; a public repository does not by itself mean the software is free or open source. Connected APIs and hosted services may have separate charges.
What can MCP Apache Spark History Server MCP Server do?: MCP Apache Spark History Server MCP Server documents 19 tools to the agent, including aws_analyze_spark_workload, aws_spark_code_recommendation, compare_job_environments. The descriptions above come from project documentation. A live handshake does not test individual tool behavior.