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Alternatives to genesys-mcp

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    Related Servers

    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants to build and manage Genesys Cloud resources such as queues, skills, users, wrap-up codes, and Architect flows through natural language, including flow diagramming and server-side publishing.
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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI clients to build and manage Genesys Cloud resources—queues, skills, users, Architect flows, outbound campaigns, and agentic virtual agents—through natural language, with real integrations and no mocks.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables building and configuring NiCE CXone tenant resources—skills, outbound dialer config, agents, teams, campaigns, DNC groups, calling lists, and Studio IVRs—from plain English via MCP, with diagramming and server-side validation. Read-only operations and safe writes are supported, while destructive actions and dialing ignition are deliberately blocked.
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server for Genesys Cloud that enables AI assistants to build and manage queues, skills, users, wrap-up codes, and Architect flows, including a flow builder that renders diagrams and publishes via Genesys' validation pipeline.
      18
      MIT
    • F
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that puts your Genesys Cloud org under AI control, enabling natural language creation of queues, skills, users, wrap-up codes, and Architect IVR flows with Mermaid diagrams.
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    • F
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that puts a Genesys Cloud org in an AI assistant's hands, enabling it to build queues, skills, users, wrap-up codes, Architect flows, and outbound contact lists, campaigns, and cadences. It composes flows as diagrams and YAML, then publishes them through Genesys' own validation pipeline.
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