get_serviceGet the full Vocenya page for a product or solution, as Markdown. Leave the slug empty to list every product page with a short description.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | The product page, like "ai-receptionist", "live-agents" or "outbound-ai-calling". |
Changes observed during successful MCP inspections.
Input schema / properties / slug / enumPrevious value: -[
- "about",
- "after-hours-answering-service",
- "ai-agents-for-small-business",
- "ai-answering-service",
- "ai-customer-service",
- "ai-receptionist",
- "appointment-booking",
- "appointment-reminders",
- "bilingual-receptionist",
- "business-phone-system",
- "conversational-ivr",
- "custom-solutions",
- "hipaa-ai-receptionist",
- "how-it-works",
- "integrations",
- "lead-qualification",
- "live-agents",
- "live-chat",
- "outbound-ai-calling",
- "outbound-lead-qualification",
- "shopify-ai-receptionist",
- "virtual-receptionist",
- "whatsapp"
-]New value: +[
+ "about",
+ "after-hours-answering-service",
+ "ai-agents-for-small-business",
+ "ai-answering-service",
+ "ai-customer-service",
+ "ai-receptionist",
+ "appointment-booking",
+ "appointment-reminders",
+ "bilingual-receptionist",
+ "business-phone-system",
+ "conversational-ivr",
+ "custom-solutions",
+ "hipaa-ai-receptionist",
+ "how-it-works",
+ "integrations",
+ "lead-qualification",
+ "live-agents",
+ "live-chat",
+ "outbound-ai-calling",
+ "outbound-lead-qualification",
+ "shopify-ai-receptionist",
+ "virtual-receptionist",
+ "whatsapp",
+ "why-vocenya"
+]Input schema / properties / slug / enumPrevious value: -[
- "about",
- "after-hours-answering-service",
- "ai-agents-for-small-business",
- "ai-answering-service",
- "ai-customer-service",
- "ai-receptionist",
- "appointment-booking",
- "appointment-reminders",
- "bilingual-receptionist",
- "business-phone-system",
- "conversational-ivr",
- "custom-solutions",
- "hipaa-ai-receptionist",
- "how-it-works",
- "integrations",
- "lead-qualification",
- "live-agents",
- "live-chat",
- "outbound-ai-calling",
- "outbound-lead-qualification",
- "virtual-receptionist",
- "whatsapp"
-]New value: +[
+ "about",
+ "after-hours-answering-service",
+ "ai-agents-for-small-business",
+ "ai-answering-service",
+ "ai-customer-service",
+ "ai-receptionist",
+ "appointment-booking",
+ "appointment-reminders",
+ "bilingual-receptionist",
+ "business-phone-system",
+ "conversational-ivr",
+ "custom-solutions",
+ "hipaa-ai-receptionist",
+ "how-it-works",
+ "integrations",
+ "lead-qualification",
+ "live-agents",
+ "live-chat",
+ "outbound-ai-calling",
+ "outbound-lead-qualification",
+ "shopify-ai-receptionist",
+ "virtual-receptionist",
+ "whatsapp"
+]Input schema / properties / slug / enumPrevious value: -[
- "about",
- "after-hours-answering-service",
- "ai-agents-for-small-business",
- "ai-answering-service",
- "ai-receptionist",
- "appointment-reminders",
- "bilingual-receptionist",
- "business-phone-system",
- "custom-solutions",
- "hipaa-ai-receptionist",
- "how-it-works",
- "integrations",
- "live-agents",
- "live-chat",
- "outbound-ai-calling",
- "virtual-receptionist",
- "whatsapp"
-]New value: +[
+ "about",
+ "after-hours-answering-service",
+ "ai-agents-for-small-business",
+ "ai-answering-service",
+ "ai-customer-service",
+ "ai-receptionist",
+ "appointment-booking",
+ "appointment-reminders",
+ "bilingual-receptionist",
+ "business-phone-system",
+ "conversational-ivr",
+ "custom-solutions",
+ "hipaa-ai-receptionist",
+ "how-it-works",
+ "integrations",
+ "lead-qualification",
+ "live-agents",
+ "live-chat",
+ "outbound-ai-calling",
+ "outbound-lead-qualification",
+ "virtual-receptionist",
+ "whatsapp"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely new behavior: the return format is Markdown, and omitting the slug changes the result shape into a list of all product pages with short descriptions. It does not discuss pagination or size limits for the full-page fetch, but the dual-mode disclosure is substantive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero filler. The core action and return type come first, and the alternate empty-slug mode follows immediately. Nothing redundant is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must carry the return-shape burden, and it does: full page as Markdown, or a list with short descriptions when slug is omitted. With a single optional enum parameter and safety already declared in annotations, nothing needed for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the enum of 24 slugs is fully self-documenting, so the baseline is 3. The description goes beyond the schema by explaining that an empty slug is legal and switches the tool into list mode — a semantic the schema itself does not state, since the schema only describes slug as a page identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: retrieves the full Vocenya page for a product or solution, returned as Markdown. The resource ('product or solution page') is distinguishable in practice from siblings like get_article and get_industry, but the description never names or contrasts those siblings, so differentiation is left to inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives one useful usage rule — leave the slug empty to list all product pages — which tells the agent how to switch into browse mode. However, it offers no guidance on when to prefer this tool over get_article, get_industry, or search_industries, so the agent must infer selection from the resource noun alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.