MCP For Claude Marketplace
Agent DAG Scheduler

Agent DAG Scheduler MCP Connector for Claude

A+

A deterministic engine for calculating execution order and scheduling metrics for multi-agent workflows.

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

This MCP server provides a deterministic execution engine for multi-agent workflows based on Directed Acyclic Graphs (DAGs). It allows AI agents to calculate the exact execution order using topological sort, determine the critical path duration, and simulate wall-clock time based on available parallel slots. Use analyze_workflow_structure to validate graph integrity and detect cycles, simulate_execution_schedule to model resource utilization and efficiency, or get_task_timing_details to inspect specific temporal constraints like slack time.

dagschedulingworkflowmulti-agenttopological-sort

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

get_task_timing_details

Provides a deep dive into the temporal constraints of a specific task within a specific schedule

analyze_workflow_structure

Validates the integrity of the provided task graph and determines the fundamental execution sequence

simulate_execution_schedule

Calculates the actual timing and resource utilization of the workflow given a limited number of execution slots

See how to talk to your AI agent using Agent DAG Scheduler.

Check if this set of tasks is a valid DAG: [{'id': 'A', 'duration': 10, 'deps': []}, {'id': 'B', 'duration': 5, 'deps': ['A']}, {'id': 'A', 'duration': 10, 'deps': ['B']}]

{"is_dag": false, "cycle_path": ["A", "B", "A"]}

Simulate a schedule for these tasks with 2 parallel slots: [{'id': 'T1', 'duration': 10, 'deps': []}, {'id': 'T2', 'duration': 10, 'deps': []}, {'id': 'T3', 'duration': 10, 'deps': ['T1', 'T2']}]

{"wall_clock_time": 20, "efficiency": 0.5}

What is the slack time for task T2 in this schedule?

{"task_id": "T2", "duration": 10, "earliest_start": 0, "latest_start": 0, "slack_time": 0}

The `simulate_execution_schedule` tool calculates how tasks are distributed across a specified number of parallel slots, accounting for both dependency constraints and resource availability.

Related Connectors

Innovation Time-to-Market Engine

Innovation Time-to-Market Engine MCP

4 tools Official

Calculate and optimize product development timelines, critical paths, and acceleration strategies.

A+ View details →
Agent Timeout & Cascading Delay Calculator

Agent Timeout & Cascading Delay Calculator MCP

3 tools Official

Calculate deterministic timeout allocations and predict cascading delays in multi-agent workflows.

A+ View details →
Agent Tool Selection Router

Agent Tool Selection Router MCP

3 tools Official

A deterministic engine for selecting and sequencing optimal tools for AI agents.

A+ View details →
Consensus Round Calculator

Consensus Round Calculator MCP

4 tools Official

Simulate and calculate Raft consensus rounds, quorum thresholds, and election timings.

A+ View details →