cognigy-plugin

Use when adding custom logic inside a Cognigy tool branch with manage_flow_nodes — supported node types, config schemas, placement rules, and the tool-first workflow.

Use when the user wants to add xApps to a Cognigy flow — interactive HTML / Adaptive Card mini-apps rendered to the user, with the submitted data flowing back into the conversation. Covers the xApp flow nodes, the Init Session rule, and accessing xApp data.

Add a new MCP tool (or extend an existing one) in the NiCE Cognigy Plugin's MCP server

Use when the user wants to build, create, or set up a new Cognigy AI Agent from scratch — covers listing projects, ensuring an LLM exists, creating the agent, testing it, and refining persona/job fields.

Use when the user wants to add knowledge, RAG, or a knowledge store/source to a Cognigy agent — covers embedding vs Knowledge Search models, Knowledge AI settings, ingesting sources, and attaching knowledge as a tool.

Use when configuring or choosing an LLM for a Cognigy agent — valid provider names (openAI, anthropic, azureOpenAI, google, mistral), model strings, connection types, and credential resolution.

Use when exporting, importing, uploading, inspecting, or downloading Cognigy package zip files — including reusing an LLM plus its connection across projects.

Use when configuring project-level Cognigy settings — voice preview / speech provider configuration and Knowledge AI settings.

Use when creating or configuring Cognigy agent tools — choosing the tool type (tool, http, mcp, knowledge, send_email) and their configuration schemas.

Use when a Cognigy agent returns empty responses, a tool call or create_ai_agent fails, a resource is not found, setup_llm fails, or you need to diagnose a Cognigy MCP problem.

Use when the user wants to set up a voice agent or a Voice Gateway endpoint with WebRTC for browser-based voice interaction.

Use when the user wants to audit, validate, or make a Cognigy voice agent production-ready against the Voice Go-Live Checklist, or asks what audit_voice_agent checks and which items are auto-fixable vs manual.

Use when the user wants to deploy a Cognigy agent to a Webchat endpoint — creating or updating the endpoint, style presets, layout/behavior settings, and the embed snippet.