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.
AI agents call conversation_sentiment to retrieve information from Genesys Cloud MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns pre-computed sentiment analysis data about conversations. It has no side effects, cannot modify data, execute code, or affect business operations. The blast radius of misuse is minimal — an agent could retrieve sentiment data it shouldn't access, but this is an access control issue rather than an inherent capability risk. Classified as Read with low severity.
From the tool's definition Tool description states it 'Retrieves sentiment analysis scores' and 'The result includes both a numeric sentiment score and an interpreted sentiment label' — pure retrieval with no modification, creation, deletion, or execution of external operations.
Documented attack patterns abuse exactly the kind of access conversation_sentiment gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Genesys Cloud MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for conversation_sentiment:
{
"version": "1",
"default": "deny",
"tools": {
"conversation_sentiment": {}
}
}conversation_sentiment is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
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. It is categorised as a Read tool in the Genesys Cloud MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Genesys Cloud MCP Server MCP server in PolicyLayer and add a rule for conversation_sentiment: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Genesys Cloud MCP Server. Nothing to install.
conversation_sentiment is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the conversation_sentiment rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for conversation_sentiment. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
conversation_sentiment is provided by the Genesys Cloud MCP Server MCP server (makingchatbots/genesys-cloud-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Genesys Cloud MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
10 Genesys Cloud MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.