MCP For Claude Marketplace
Map-Reduce Partition Planner

Map-Reduce Partition Planner MCP Connector for Claude

A+

Deterministic calculator for partitioning and scheduling map-reduce workloads.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides precise mathematical modeling for distributed computing workloads. It allows AI agents to calculate optimal data partitioning, estimate network shuffle volumes, and project total execution times for map-reduce pipelines. Use plan_workload_partitioning to determine how to distribute records across agents, calculate_shuffle_volume to estimate data transfer requirements, and estimate_execution_time to predict the duration of the entire processing pipeline.

map-reducepartitioningdata-processingschedulingdistributed-systems

3 tools expose this connector's capabilities to your AI agent.

calculate_shuffle_volume

estimate_execution_time

plan_workload_partitioning

See how to talk to your AI agent using Map-Reduce Partition Planner.

I have 1,000,000 records and 10 map agents. How many records will each map agent process?

Each map agent will process 100,000 records.

Calculate the shuffle volume for 500,000 records with an average size of 1024 bytes.

The total shuffle volume is 512,000,000 bytes, which is approximately 488.28 MB.

If a map agent has 5,000 records and processing takes 0.01 seconds per record, how long is the map phase?

The map phase will take 50 seconds.

The `plan_workload_partitioning` tool calculates a skew ratio. If the ratio exceeds 3, it flags the reducer as 'hot', indicating that you should consider salting keys to balance the load.

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