Vendor-neutral catalog of 300+ commercial robots: search, compare specs, request vendor intros.
Scored across 5 tools
Each tool targets a clearly distinct operation: finding robots, viewing one robot in detail, comparing two robots, exploring categories, and submitting a sourcing request. Though get_robot and compare_robots both access robot data, their purposes are unambiguous from their descriptions.
All tool names follow a consistent lower_snake_case verb_noun pattern: compare_robots, get_robot, list_categories, request_vendor_intros, search_robots. The minor singular/plural difference in objects does not detract from the predictability.
Five tools is a well-scoped size for a catalog-focused server: three core read operations, one comparison helper, and one conversion action. Each tool earns its place and there is no bloat.
The domain is browsing and sourcing from a robot catalog, and the surface covers discovery (search, list categories), deep retrieval (get_robot), comparison (compare_robots), and the primary conversion action (request_vendor_intros). There are no obvious dead ends for the stated purpose.
Side-by-side spec comparison of two robots by slug, plus RoboHub's editorial verdict when available.
| Name | Required | Description | Default |
|---|---|---|---|
| slug_a | Yes | First robot slug. | |
| slug_b | Yes | Second robot slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist; description implies read-only behavior by stating comparison. However, does not explicitly disclose non-destructive nature or any constraints like rate limits or permissions.
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?
Single, concise sentence with no wasted words. Front-loads the core action and includes a relevant extra 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 simple tool with two parameters and no output schema, description covers basic purpose but lacks detail on return format or what 'specs' means. Adequate but could be more complete.
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 already fully describes parameters (slug_a, slug_b) with 'First/Second robot slug.' Description adds 'by slug' which is consistent but does not enhance meaning beyond schema.
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?
Description clearly states verb 'compare', resource 'two robots', method 'by slug', and additional output 'editorial verdict'. Distinguishes from sibling tools that handle single robots or search.
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?
Implies use for comparing two known robots by slug, but no explicit when-to-use or alternatives listed. Sibling names are provided but not referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Full catalog record for one robot by slug: description, specs, SDKs, use cases, pricing and links.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Robot slug as returned by search_robots (e.g. 'unitree-g1'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It accurately describes the return content but does not explicitly state read-only nature, absence of side effects, or error handling. Adequate for a simple retrieval tool.
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?
Single, informative sentence with no wasted words. Front-loaded with key information.
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 tool with one parameter and no output schema, the description sufficiently explains what is returned. Could mention result format but not critical.
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%, with the schema already describing the slug parameter and providing an example. The description reinforces its source but adds minimal new 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?
The description clearly states it retrieves a full catalog record for one robot by slug, listing specific details (description, specs, SDKs, use cases, pricing, links). It distinguishes from siblings like search_robots (list) and compare_robots (comparison).
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 implies use after search_robots by referencing slug from that tool. Sibling tools are listed, providing context. However, it does not explicitly state when not to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
All robot categories with counts and a few example robots each. Good first call to understand catalog coverage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions it returns counts and examples, but does not disclose read-only nature, auth requirements, or side effects. As a listing tool, behavior is likely safe, but transparency is minimal.
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, direct and to the point. Every word adds value with no redundancy.
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?
Description covers purpose and typical use case. No output schema exists, so the description should hint at return format; it does so with 'counts and a few example robots.' Lacks detail on structure but sufficient for a simple list 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?
Tool has no parameters, so schema coverage is 100%. Description adds context about what is returned (counts, examples), which is sufficient for this zero-parameter tool.
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?
Description clearly states the tool lists all robot categories with counts and example robots. Differentiates from sibling tools like compare_robots and get_robot by focusing on catalog overview.
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?
Describes as a 'good first call to understand catalog coverage,' implying its role as an initial exploratory tool. Lacks explicit when-not-to-use or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Record a B2B sourcing request with RoboHub on behalf of the user, for manual review by RoboHub's team. Vendor-neutral and free for buyers. Requests from this server are unverified, so RoboHub sends the buyer no confirmation email and guarantees no reply window. Only call this with the user's explicit consent and their real contact details; submissions are rate limited per client and fabricated requests are discarded.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Work email address where the shortlist should be sent. | ||
| notes | No | Anything else relevant (optional). | |
| company | Yes | Company name. | |
| country | No | Country of deployment (optional). | |
| industry | Yes | Closest industry bucket for the deployment. | |
| timeline | Yes | Deployment timeline. | |
| use_case | Yes | What the robots should do, with as much operational detail as possible (environment, scale, constraints). | |
| robot_slug | No | Slug of a specific robot the user is interested in (optional). | |
| budget_range | Yes | Approximate budget bracket in USD. | |
| contact_name | Yes | Full name of the contact person. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so thoroughly: it discloses that requests are unverified, no confirmation email is sent, no reply window is guaranteed, submissions are rate limited, and fabricated requests are discarded. This is unusually candid and helps the agent set accurate expectations.
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 three dense sentences with no filler. It front-loads the core purpose, then provides the vendor-neutral and free context, then the critical consent and behavioral caveats.
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 manual-review submission tool with 10 parameters and no annotations, the description covers workflow, caveats, consent, and failure modes well. The only minor gap is that it does not describe what response or confirmation the agent should expect after submission, though the 'no confirmation email' note partially addresses this.
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%, so the schema already documents all parameters. The description adds a real-contact-details and consent requirement, which indirectly relates to email and contact_name, but it does not add new parameter-level 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 clearly states a specific action ('Record a B2B sourcing request... for manual review') and names the target system (RoboHub). It is easily distinguished from the sibling catalog/search tools, which serve a different purpose.
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 gives clear context for when to call the tool and adds an explicit gate: only call with the user's explicit consent and real contact details. It does not name alternatives, but the sibling tools are robot-information tools, so the intended use is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search RoboHub's catalog of commercial robots by free-text query and optional filters. Returns compact summaries with catalog URLs. Note: robots with unknown pricing are excluded when max_price_usd is set.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (default 10, max 25). | |
| query | No | Free-text search over name, manufacturer, category, use cases and description (e.g. 'warehouse pallet AMR', 'quadruped inspection'). | |
| category | No | Restrict to one category. | |
| max_price_usd | No | Only robots with a known price at or below this USD amount. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses the pricing exclusion behavior but omits details on rate limits, pagination, or what happens with no results. It's a read operation but not explicitly labeled.
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, no fluff. The purpose is front-loaded, and the important behavioral note is placed at the end. Every sentence earns its 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?
Given no output schema, the description mentions return format (compact summaries with URLs) and pricing exclusion. It's sufficient for a search tool but could note pagination or result count limits beyond the parameter.
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 each parameter has a description. The description adds value by giving examples for the query field and clarifying how max_price_usd excludes unknown-priced robots. This enriches the schema data.
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 searches RoboHub's catalog of commercial robots via free-text query and optional filters, returning compact summaries with catalog URLs. It distinguishes itself from siblings like get_robot (single robot) and list_categories.
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 explains the tool's function but provides no explicit guidance on when to use it vs. alternatives like compare_robots or get_robot. It implies usage via search but lacks when-not-to-use or trade-offs.
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.
request_vendor_intros2 fields changedInput schema / properties / industry / descriptionPrevious value: -"Industry, e.g. 'logistics', 'agriculture', 'security', 'hospitality'."New value: +"Closest industry bucket for the deployment."Input schema / properties / industry / enumAdded value: +[
+ "manufacturing",
+ "warehouse",
+ "healthcare",
+ "agriculture",
+ "security",
+ "hospitality",
+ "construction",
+ "energy",
+ "research",
+ "other"
+]compare_robotsget_robotlist_categoriesrequest_vendor_introssearch_robotsMarket & supply-chain intelligence on 34 humanoid robots: scores, specs, pricing. No key.
Evidence-based humanoid robot data: RadarScore ratings, evidence grades A-D, prices, EU availability
Checkout-verified prices, stock, US FCC status and buy routes for humanoid and quadruped robots
Cross-vendor B2B catalog for AI agents: search, compare, find equivalents, request a quote.
Add one secure layer between your agents and this server.
