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fsubzwari19
by fsubzwari19

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Alternatives to genesys-mcp

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables building and managing Genesys Cloud resources—such as queues, skills, users, Architect flows, outbound campaigns, and agentic virtual agents—through natural language from any MCP client, including diagramming and publishing via Genesys' own pipelines.
      MIT
    • 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
      C
      maintenance
      Enables AI clients to build and manage Genesys Cloud resources such as queues, skills, users, wrap-up codes, Architect flows, outbound campaigns and cadences, and agentic virtual agents end to end. It provides tools for creating, validating, diagramming, testing, and publishing these resources through Genesys Cloud APIs.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI assistants to build and manage Genesys Cloud resources such as queues, skills, users, wrap-up codes, Architect flows, and outbound campaign cadences, while deliberately preventing deletes and leaving campaigns off until humans start them.
      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.
      4
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI clients to build and manage a Genesys Cloud org end to end through natural language — queues, skills, users, wrap-up codes, Architect call flows, outbound contact lists, campaigns and cadences, and agentic virtual agents. It composes real Archy YAML, renders Mermaid diagrams in chat, and publishes through Genesys' own pipelines, while leaving campaigns off and AVA versions at TestReady for human review.
      MIT