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Load Balancer Distributor

Load Balancer Distributor MCP Connector for Claude

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Deterministic simulation engine for evaluating load balancing algorithms.

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

This MCP server provides a deterministic simulation engine to evaluate how various load-balancing algorithms distribute weighted tasks across a pool of agents. Use simulate_distribution to calculate exact task-to-agent assignments and performance metrics like load variance and saturation. You can also use get_agent_status to inspect agent utilization or validate_system_constraints to verify if a distribution plan is feasible without exceeding agent capacities.

load-balancingdeterministicsimulationalgorithmsagents

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

validate_system_constraints

Checks if a proposed set of tasks can be distributed without any agent exceeding its absolute capacity

get_agent_status

Provides a snapshot of the current state of all agents to prepare for a simulation

simulate_distribution

Calculates the exact assignment of tasks to agents using a specific algorithm and returns performance metrics

See how to talk to your AI agent using Load Balancer Distributor.

Simulate a distribution using round_robin for these agents: [{'id': 'a1', 'capacity': 100, 'currentLoad': 10, 'latencyMs': 5}] and these tasks: [{'id': 't1', 'weight': 20, 'affinityKey': 'k1'}]

{ "assignments": [ { "taskId": "t1", "agentId": "a1" } ], "loadVariance": 0, "maxLoadRatio": 0.3, "affinityPreservation": 100, "isSaturated": false }

Check the status of agent 'a1'.

{ "agentId": "a1", "utilization": 0.1, "totalLoad": 10 }

Is it feasible to assign a task with weight 95 to an agent with capacity 100 and current load 10 using least_connections?

{ "isFeasible": false, "bottleneckAgentId": "a1" }

The engine supports round_robin, weighted_round_robin, least_connections, consistent_hash, and power_of_two_choices.

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