mcp-apache-spark-history-server vs filesystem

Side-by-side comparison to help you pick between these two MCP servers.

	mcp-apache-spark-history-server by kubeflow	filesystem by modelcontextprotocol
Stars	★ 170	★ 85,748
30d uses	—	—
Score	50	77
Official	—	✓
Categories	Developer ToolsMonitoringAI / LLM Tools	File SystemDeveloper ToolsProductivity
Language	Python	TypeScript
Last commit	this month	this month

mcp-apache-spark-history-server · Summary

MCP Server connecting AI agents to Apache Spark History Server for job analysis and performance monitoring.

filesystem · Summary

A feature-rich MCP server for filesystem operations with dynamic directory access control.

mcp-apache-spark-history-server · Use cases

AI agents investigating failed or slow Spark applications using natural language queries
Comparing performance metrics between different Spark job runs to identify regressions
Automating Spark job monitoring and alerting through integration with AI agents

filesystem · Use cases

Enable AI models to read and write project files during development
Allow Claude or other MCP clients to browse and analyze codebases
Provide secure sandboxed access to specific directories for content generation

mcp-apache-spark-history-server · Install

Install with pip:

pip install mcp-apache-spark-history-server
spark-mcp

Run directly with uvx (no install needed):

uvx --from mcp-apache-spark-history-server spark-mcp

Configuration via config.yaml (supports multiple servers):

servers:
  local:
    default: true
    url: "http://your-spark-history-server:18080"
    auth:
      username: "user"
      password: "pass"
mcp:
  transports:
    - streamable-http
  port: "18888"

Claude Desktop configuration:

{
  "mcpServers": {
    "spark": {
      "command": "spark-mcp",
      "args": []
    }
  }
}

filesystem · Install

Installation

Using NPX

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/directory"
      ]
    }
  }
}

Using Docker

{
  "mcpServers": {
    "filesystem": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--mount", "type=bind,src=/path/to/allowed/dir,dst=/projects/allowed/dir",
        "mcp/filesystem",
        "/projects"
      ]
    }
  }
}

VS Code Extension

Click the installation buttons in the README to install directly in VS Code.

Comparison generated from public README + GitHub signals. Last updated automatically.