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genpark-page-rank-power-iteration-centrality-skill

genpark-page-rank-power-iteration-centrality-skill

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      Enables agents to resolve dependencies and analyze directed graphs through topological sorting, strongly connected components, shortest paths, maximum flow, minimum spanning trees, and centrality ranking via MCP.
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    • A
      license
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      Enables agents to compute shortest paths with Dijkstra and A*, resolve DAG dependencies, solve maximum flow, build minimum spanning trees, and rank graph centrality using JSON-RPC MCP tools.
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      Enables agents to compute shortest paths, topological dependency order, maximum flow and minimum-cut bottlenecks, minimum spanning trees, and PageRank centrality over weighted graphs for routing and execution planning. It exposes these graph-analysis capabilities as MCP tools through a zero-dependency Python server.
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    • A
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      Enables agents to compute shortest paths, topological orderings, maximum flow and minimum cut bottlenecks, minimum spanning trees, and centrality rankings for graph-based multi-agent routing. It runs as a zero-dependency MCP server using standard Python libraries.
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    • A
      license
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      Enables MCP clients to run zero-dependency graph algorithms—including topological sorting, strongly connected component detection, shortest paths, maximum flow, minimum spanning trees, and PageRank—for agent dependency resolution and execution planning.
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