What authentication does the server require?
You must create an OAuth Client in Genesys Cloud, assign needed permissions, and provide its ID, secret, and region as environment variables.
@MakingChatbots
基本情報
Model Context Protocol (MCP) server for Genesys Cloud’s Platform API
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"genesys-cloud": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@makingchatbots/genesys-cloud-mcp-server"
],
"env": {
"GENESYSCLOUD_REGION": "<PUT REGION HERE>",
"GENESYSCLOUD_OAUTHCLIENT_ID": "<PUT OAUTHCLIENT ID HERE>",
"GENESYSCLOUD_OAUTHCLIENT_SECRET": "<PUT OAUTHCLIENT SECRET HERE>"
}
}
}
}Searches for routing queues based on their name, allowing for wildcard searches. Returns a paginated list of matching queues, including their Name, ID, Description (if available), and Member Count (if available). Also provides pagination details like current page, page size, total results found, and total pages available. Useful for finding specific queue IDs, checking queue configurations, or listing available queues.
Retrieves conversation analytics for a specific queue between two dates, returning a representative sample of conversation IDs. Useful for reporting, investigation, or summarisation.
Returns a breakdown of how many conversations occurred in each specified queue between two dates. Useful for comparing workload across queues. MAX 300 queue IDs.
Retrieves voice call quality metrics for one or more conversations by ID. This tool specifically focuses on voice interactions and returns the minimum Mean Opinion Score (MOS) observed in each conversation as structured JSON. MOS is a measure of perceived audio quality based on factors such as jitter, latency, packet loss, and codec. Use the following legend to interpret MOS values: • Poor: MOS < 3.5 • Acceptable: 3.5 ≤ MOS < 4.3 • Excellent: MOS ≥ 4.3
Retrieves sentiment analysis scores for one or more conversations. Sentiment is evaluated based on customer phrases, categorized as positive, neutral, or negative. The result includes both a numeric sentiment score (-100 to 100) and an interpreted sentiment label.
Retrieves Speech and Text Analytics topics detected for a specific conversation. Topics represent business-level intents (e.g. cancellation, billing enquiry) inferred from recognised phrases in the customer-agent interaction.
Searches for voice conversations within a specified time window, optionally filtering by phone number. Returns a paginated list of conversation IDs and call duration for use in further analysis or tool calls.
Retrieves a structured transcript of the conversation, including speaker labels, utterance timestamps, and sentiment annotations where available. The transcript is formatted as a time-aligned list of utterances attributed to each participant (e.g., customer or agent)
Retrieves a list of all OAuth clients, including their associated roles and divisions. This tool is useful for auditing and managing OAuth clients in the Genesys Cloud organization.
Retrieves the usage of an OAuth Client for a given period. It returns the total number of requests and a breakdown of Platform API endpoints used by the client.
An MCP server that exposes Genesys Cloud Platform API tools to AI assistants like Claude Desktop and Gemini CLI. It is a personal project under active development for conversational Business Insights.
Install via the provided MCP bundle (.mcpb file) or via NPX by configuring GENESYSCLOUD_REGION, GENESYSCLOUD_OAUTHCLIENT_ID, and GENESYSCLOUD_OAUTHCLIENT_SECRET environment variables. The server runs over stdio.
You must create an OAuth Client in Genesys Cloud, assign needed permissions, and provide its ID, secret, and region as environment variables.
Download the `.mcpb` file from the latest release and open it with Claude Desktop, or add the NPX command to your `claude_desktop_config.json` or Gemini `settings.json`.
Currently only stdio transport is supported.
No, it is a personal project under active development and may change frequently.
Node.js is required to run via NPX; no additional dependencies are noted.
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