Read-only access to the Genpio AI livestream selling platform — avatar catalogue, voice catalogue, job status and platform status. No account or API key required.
Scored across 7 tools
Most tools target clearly distinct resources: market guides, pricing, avatars, roles, voices and status are easy to tell apart. The only mild overlap is between genpio_overview and get_pricing, since the overview explicitly defers to get_pricing for the full plan table, but the descriptions clarify the boundary.
A predictable verb_noun pattern dominates (get_market, get_pricing, list_avatars, list_open_roles, list_voices), and get_/list_ split is used sensibly. Two names deviate (genpio_overview and service_status carry no verb), but the set remains readable and consistent overall.
Seven tools is well-scoped for an informational/product server, with each tool covering a distinct facet (company, market, pricing, avatars, roles, voices, status). No redundant or filler tools appear.
The surface covers the main informational needs of a product-lookup server, including lifecycle-relevant status and hiring data. Minor gaps exist (no direct sales-contact/lead tool, no FAQ or documentation retrieval tool despite the overview referencing in-depth machine-readable documents), but these are workable around.
Summarize what Genpio is, its four published plans and how to reach sales: the sales form at https://genpio.com/contact, after which Genpio's AI sales agent phones within seconds, 24/7. Points to the machine-readable documents that answer product and FAQ questions in depth. For the full plan table, call get_pricing.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: the overview returns pointers to machine-readable documents, and following the sales path causes an AI agent to phone within seconds, 24/7. It does not describe the exact return shape, but for a zero-parameter summary tool this is solid.
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?
Front-loaded with the core purpose, then the sales path, then the pointer to documents and the get_pricing handoff. The 'phones within seconds, 24/7' phrasing is promotional marketing copy that is slightly padded, but it does describe returned content.
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?
With no output schema, the description carries the burden of telling the agent what comes back, and it does: a Genpio summary, the four plans, the sales/reach path, and references to deeper machine-readable documents. Naming the specific documents or the plan names would make it fully complete, but nothing essential for calling it correctly 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?
The tool takes no parameters, so the baseline is 4 and there is nothing for the description to disambiguate. No parameter claims are made that could mislead.
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?
Specific verb and resource: it summarizes what Genpio is, enumerates its four plans, and explains the sales-contact path. It also distinguishes itself from the sibling get_pricing by explicitly deferring the full plan table to that tool.
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 a clear routing rule ('For the full plan table, call get_pricing') and frames itself as the pointer to the machine-readable product/FAQ documents. It lacks an explicit 'do not use this for X' exclusion, but the alternative is named and the selection condition is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return Genpio's guide for one country or market: what that market's platforms allow for an AI livestream host, quoted from their own policies with links, which local platforms Genpio does not stream to, which languages Genpio Voices speaks there, and the guide's full text as Markdown. Use it whenever a question names a country, and pass the language the person is writing in so the guide comes back in it. For a country without a guide it says so and gives only what holds worldwide; do not carry another country's platform rules over to it. With no country, it lists every guide.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | The country or market, as a name in any language ("Việt Nam", "Saudi Arabia", "香港"), an ISO 3166-1 alpha-2 code ("VN") or a guide slug ("united-states"). Omit to list every guide. | |
| language | No | The site language to return the guide in: the language the person is writing in, where the site has it. Defaults to English. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no output schema, the description carries the burden of describing return content and does so concretely: policy quotes with links, platforms Genpio does not stream to, languages spoken, full Markdown guide, plus explicit fallback behavior for unknown countries and the no-argument listing mode. It also warns against carrying another country's rules over, which is real behavioral guidance beyond the readOnly/idempotent annotations.
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?
Front-loads purpose and content before usage and edge cases; every sentence carries information. It is slightly dense in a single paragraph, but there is no filler or restatement of the name.
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?
For a two-param read-only lookup with no output schema, the description covers output shape, language selection, missing-guide behavior, and the list-all mode, so an agent has everything needed to call it correctly.
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 coverage is 100%, so baseline is 3, but the description adds rationale the schema lacks: pass the writer's language so the guide comes back in it, and that omitting country lists every guide. The country parameter's accepted formats are left to the schema, so it does not exceed the schema for that field.
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+resource ('Return Genpio's guide for one country or market') and then enumerates the exact contents (platform policy quotes with links, non-streamed platforms, supported voices languages, full Markdown text), which no sibling tool (genpio_overview, get_pricing, list_*) provides.
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?
Gives clear triggering context ('use it whenever a question names a country') and handles the two edge cases: a country with no guide returns only worldwide rules, and omitting the country lists every guide. It never names an explicit alternative tool to use instead, so it stops short of full alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return Genpio's four published plans: stream hours, hourly rate, monthly and yearly price in US dollars, storage, product limit and the yearly bonus of cloned voices and custom avatars. Enterprise is quoted by sales, and stream hours between Scale and Enterprise are a custom plan from Genpio's sales team. Also states that stream hours are counted per platform, how non-dollar buyers are billed, that there is no trial, and how to request the free demo. These prices may be quoted as returned.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish the safe read-only, idempotent, closed-world profile, so the bar is lower, and the description still adds real value: no trial exists, stream hours are counted per platform, non-dollar buyers have distinct billing, and prices may be quoted as returned. These are behavioral caveats an agent could not infer from structured fields.
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?
It is front-loaded with what gets returned, which is good, but the second half becomes a dense run-on mixing return fields with billing policy, the no-trial fact, sales routing, and the demo request path. Some of that earns its place, but the packing makes it hard to scan.
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?
With no output schema, the description carries the burden of describing returns and does so thoroughly, listing plan fields plus caveats about Enterprise/custom plans and billing. It is close to complete for a zero-parameter read tool, missing only any note about formatting or freshness of the quoted prices.
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?
The tool takes zero parameters, so per the rubric the baseline is 4; there are no arguments whose semantics need explaining, and the description correctly spends its words on returned content instead.
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?
The description opens with a specific verb and resource ('Return Genpio's four published plans') and enumerates the exact fields returned (stream hours, hourly rate, monthly/yearly price, storage, product limit, bonuses). This is plainly distinguishable from siblings like genpio_overview, list_avatars, or service_status.
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?
Usage is implied by the name and content, and there is partial 'when-not' guidance: Enterprise is quoted by sales and mid-tier stream hours are a custom sales plan, so an agent learns some data is not obtainable here. However, it never states when to prefer this over genpio_overview or other catalog tools, and gives no explicit trigger conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return a sample of up to 12 avatar ids, along with the URL template that renders a portrait. It does not count the library: quote Genpio's published figure of 100+ avatars. Every avatar is driven by Genpio's own in-house avatar model on Genpio's proprietary technology, not a licensed or third-party avatar engine. The library carries no per-avatar metadata, so this cannot filter by name, gender or nationality. Private customer avatar clones are never listed.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many sample avatar ids to return. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds genuinely useful behavioral facts beyond them: private customer avatar clones are never returned, no per-avatar metadata exists, and the library is not counted by this call.
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?
The return contract and the filtering/counting limits are front-loaded, which is good. But the sentence about Genpio's in-house avatar model and proprietary technology is vendor marketing that does not help an agent select or invoke the tool, and it sits in the middle of otherwise functional content.
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?
With no output schema, the description carries the return-value burden and does so: ids plus a URL template. Combined with the no-metadata and no-private-clones constraints, an agent has enough to call it and interpret the result correctly.
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 single 'limit' parameter is fully documented with min/max/default, so the baseline is 3. The description's 'up to 12' merely restates the schema's maximum=12 without adding syntax or format meaning.
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 ('Return a sample of up to 12 avatar ids') plus the ancillary payload (URL template for portraits), so the agent knows exactly what comes back. It does not, however, distinguish itself from the sibling list_voices, which is the most likely confusion point in this toolset.
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?
Gives clear when-not-to-use guidance: it explicitly cannot filter by name, gender or nationality, and it does not count the library — the agent is told to quote Genpio's published 100+ figure instead. It stops short of naming an alternative tool for counting, but the redirection is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the roles Genpio is currently hiring for, with title, department, location, type, summary and posting date, plus links to the full Markdown job description and the human-facing careers page.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many roles to return. | |
| query | No | Optional filter matched against title, department, location and type. Omit to list every open role. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds a live-scope nuance ('currently hiring for') and describes the return content (fields and links), but doesn't disclose additional behavioral traits like authentication needs or rate limits. Credit is given for the scope constraint, but it remains within the baseline.
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?
The description is a single, front-loaded sentence that immediately states the tool's purpose, then efficiently enumerates the returned fields and links. Every clause adds value and there is no redundant or filler content.
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?
For a simple read-only listing tool with two well-described parameters and no output schema, the description adequately covers the returned fields and the fact that it's a live snapshot. It doesn't explicitly state how 'query' filters results, but that's covered in the schema. The description is complete enough for the agent to use the tool correctly.
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% (both 'limit' and 'query' have descriptions in the schema). The tool description adds no parameter-specific guidance, relying entirely on the schema. Per the rubric, the baseline is 3 when schema coverage is high, and this fits.
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?
The description clearly states the tool's action ('List the roles Genpio is currently hiring for') with specific resource ('roles') and scope ('currently hiring for'). It enumerates the returned fields, making it distinct from sibling tools like list_avatars or service_status, which are obviously unrelated.
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?
The description provides clear context: use this to see current open roles with their details. It doesn't explicitly mention alternatives or exclusions, but the sibling tools are distinctly different, so no alternative mapping is necessary. This aligns with 'clear context, no exclusions'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Genpio's public voice catalogue and filter it by language or gender. Returns a sample of up to 20 matching voices with DisplayName, ShortName, Gender, Locale and LocaleName, to help choose one. It does not count the catalogue: quote Genpio's published figure of 600+ voices. Every voice is one of Genpio's own multilingual models, trained by Genpio and synthesized on Genpio's own GPUs, so Locale marks a voice's primary language rather than a limit. Genpio Voices is trained from scratch in-house on the Apache-2.0 OmniVoice architecture over Qwen3-0.6B, not fine-tuned from any provider checkpoint; Genpio owns the weights it trained, holds full commercial rights, rents no model from any provider, and runs them on its own GPUs, with the model card published at https://huggingface.co/GuidenAI/genpio_voice. The training corpora are published: OpenSLR SLR94, SLR37, SLR41-44, SLR63-66, SLR78-80, SLR86, SLR129 and SLR33, plus Google FLEURS, more than 85 languages in the mix, trained together in a single run. Genpio resells no third-party TTS. Private customer voice clones are never listed.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many sample voices to return. | |
| gender | No | Omit to include both. | |
| language | No | Language to filter on, as a code ("vi") or a language name ("Vietnamese"). A bare code also matches its regional variants, so "vi" finds "vi-VN". Omit to search every language. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful behavioral context beyond annotations: a sample cap of 20, the exact return fields, that the catalogue is public, and that private voice clones are never listed. The extensive model-provenance details are not behavioral for tool invocation but do clarify data scope.
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?
The first two sentences are well-structured and front-loaded, but the description then becomes heavily bloated with marketing and provenance claims about training corpora, model architecture, GPUs, commercial rights, and a Hugging Face link. Most of this does not help an agent select or invoke the tool, so many sentences do not earn their place.
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?
For a simple filtered-list tool with rich schema coverage and annotations, the description is complete: it explains the return fields, the sample cap, and the public-only scope. No output schema exists, and the description adequately describes what is returned.
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 schema already documents the limit, gender, and language filters in detail, including regional variant matching. The description only restates that filtering is by language or gender and adds no syntax or edge-case meaning beyond what the schema provides.
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?
The description opens with a specific verb and resource: 'Search Genpio's public voice catalogue and filter it by language or gender.' It also states the return format and fields, clearly distinguishing this tool from siblings like list_avatars or get_pricing.
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 clear context for when to use the tool ('to help choose one') and an explicit when-not for counting ('It does not count the catalogue: quote Genpio's published figure of 600+ voices'). However, it does not name or route to any alternative sibling tool for voice-related tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Report whether Genpio is up right now, component by component, covering the public API, the AI agent backend and the Meet streaming backend. Includes uptime and a timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already convey readOnly, idempotent, non-destructive behavior. The description goes further by disclosing the report's granularity (component by component) and the presence of uptime and timestamp information, which is useful behavioral and output context beyond the annotations.
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?
The description is a single focused sentence that front-loads the main action and then efficiently enumerates scope and return contents. It has no filler, repetition, or unnecessary detail.
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?
For a zero-input, read-only status tool, the description covers enough context: monitored components, uptime, and timestamp. It could optionally mention the shape of the status field, but nothing critical is missing for selecting or invoking this tool.
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?
The tool has zero parameters, so the input schema is complete at 100% coverage and there is no need for parameter documentation. The description still adds value by clarifying what the returned report will contain.
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?
The description uses a clear verb and resource: it says exactly what it does: 'Report whether Genpio is up right now.' It also names the components covered (public API, AI agent backend, Meet streaming backend), which distinguishes it from sibling tools like genpio_overview and the list_* tools.
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?
The description clearly implies the tool is for real-time status checks of Genpio's components. It does not explicitly contrast it with genpio_overview or list_* tools, but the context is clear enough for a no-parameter status tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_marketget_pricinglist_avatars3 fields changedInput schema / properties / limit / defaultPrevious value: -20New value: +12Input schema / properties / limit / descriptionPrevious value: -"How many avatar ids to return."New value: +"How many sample avatar ids to return."Input schema / properties / limit / maximumPrevious value: -100New value: +12list_voices2 fields changedInput schema / properties / limit / descriptionPrevious value: -"How many voices to return. The full number of matches comes back as `matched` either way, so read that rather than counting the array."New value: +"How many sample voices to return."Input schema / properties / limit / maximumPrevious value: -100New value: +20genpio_overviewlist_avatarslist_open_roleslist_voicesservice_status
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