Venturu's MCP server turns AI agents into deal scouts - letting them search the Venturu marketplace for businesses up for sale, discover brokers who can guide the process, and reach out directly to sellers or brokers to get the conversation started.
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Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 9 of 9 tools scored. Lowest: 3.2/5.
Each tool targets a distinct resource and action: brokers vs businesses, search vs get vs contact, and supporting list tools for categories and languages. No two tools have overlapping purposes, and the descriptions clearly differentiate them.
Most tools follow a consistent verb_noun pattern (contact_broker, get_business, search_brokers, list_languages). The only deviation is who_am_i, which is a common idiom for identity checks but does not follow the same pattern, making it a minor inconsistency.
With 9 tools, the set is well-scoped for a business marketplace. Each tool serves a clear purpose in the search-detail-contact workflow, and there are no redundant or unnecessary tools.
The toolkit covers the full user journey: discovering categories/languages, searching for brokers/businesses, viewing details, and contacting them. It also includes authentication verification. No obvious gaps or dead ends prevent successful completion of typical tasks.
contact_brokerContact BrokerAInspectSend a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| message | Yes | ||
| inquiryType | No | buying |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate not read-only and not destructive. The description adds the need for authentication, which is a useful prerequisite. However, it doesn't describe side effects (like whether the message is actually sent outside the system), idempotency, or what happens after sending. Given the annotations cover the basic safety profile, a 3 is appropriate.
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 four sentences, each adding value: the core action, the auth requirement, the parameter options, and the pointer to search_brokers. It is front-loaded and free of filler.
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 contact-sending tool with 3 params and no output schema, the description covers purpose, usage, parameters, and how to get slugs. It lacks mention of return values or error behavior, and doesn't differentiate from sibling 'contact_seller,' but overall it's nearly 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?
With 0% schema description coverage, the description fully compensates by explaining every parameter: 'slug' (broker's profile slug), 'message' (the text to send), and 'inquiryType' (with default 'buying' and meanings for 'buying' vs 'selling'). This adds significant meaning beyond the raw 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?
The description clearly states the tool's function: 'Send a contact message to a broker on Venturu by their profile slug.' This is a specific verb and resource, and the slug mechanism is mentioned. However, it does not explicitly distinguish from the sibling tool 'contact_seller,' so it's not a full 5.
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: it requires an authenticated account, and it instructs to use 'search_brokers' to find slugs. It also explains the two inquiryType values. However, it doesn't explicitly mention when to use this vs. 'contact_seller,' so it misses the exclusion/alternative clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contact_sellerContact SellerBInspectSend a contact message to a seller on Venturu by their listing ID. Requires an authenticated Venturu account. Provide the listing ID and the message to send. Use search_businesses to find listing IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| listingId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations already indicating a non-read-only, non-destructive operation, the description adds the important requirement of an authenticated Venturu account. It does not disclose other behavioral aspects such as rate limits, success/failure responses, or side effects beyond sending a message, so transparency is only mildly enhanced.
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 concise, with four short sentences that get to the point. The inclusion of the authentication requirement and search tip are useful, though the sentence 'Provide the listing ID and the message to send' is somewhat redundant with the first sentence.
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 two-parameter tool, the description covers purpose, authentication, and how to find a listing ID. However, it does not mention what the tool returns or any side effects beyond sending, and the presence of a sibling tool (contact_broker) without differentiation leaves some contextual gaps.
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 0%, so the description must compensate. It merely repeats the parameter names ('listing ID and the message') without explaining format, constraints, or semantics beyond what the schema's basic types provide. The description adds little value for understanding the parameters.
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 action ('Send a contact message') and target ('a seller on Venturu by their listing ID'), making the purpose obvious. However, it does not differentiate from the sibling tool contact_broker, which likely serves a similar function for brokers.
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 mentions the authentication requirement and suggests using search_businesses to find listing IDs, providing some usage context. However, it does not explicitly state when to use this over contact_broker or any exclusion criteria, leaving the choice ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_brokerGet Broker DetailsAGet full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
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 little beyond that, such as error handling or return format, but does not contradict 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 exactly two sentences, front-loaded with the core purpose and followed by usage context. Every sentence serves a clear function 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?
For a simple one-parameter read-only tool, the description covers what, when, and where the input comes from. It does not detail the return structure, but with no output schema or complexity, this is a minor gap.
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 schema only provides 'slug' with minLength 1, but the description explains it is a 'profile slug' and directs the agent to use the slug from search_brokers results. This is meaningful compensation given 0% schema description coverage.
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 action ('Get full details for a single broker') and identifies the resource (broker/agent) and key parameter (profile slug). It also distinguishes itself from sibling tools like search_brokers by specifying 'single' and 'by profile slug'.
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 explicitly says 'Call this when the user asks for more information about a specific broker,' providing clear timing. It also gives an integration hint to use the slug from search_brokers results, but does not explicitly list exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_businessGet Business DetailsAGet full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds minimal behavioral context beyond the schema, such as returning 'full details', but it does not disclose error handling, authentication requirements, or rate limits. With annotations doing the heavy lifting, a score of 3 is appropriate.
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 two sentences with no filler. The first sentence states the primary purpose, and the second provides usage context and slug provenance. It is well-structured and front-loaded.
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 single-parameter read-only tool with annotations and no output schema, the description covers the essential context: what it does, when to use it, and how to get the required slug. It omits error behavior (e.g., not-found handling), but that is not critical for a simple getter. Overall, it is sufficiently complete for an agent to use 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?
The schema has one parameter (slug) with no description (0% coverage). The description compensates by explaining that the slug comes from search_businesses results, giving the agent clear guidance on how to obtain a valid value. This goes beyond the schema and is sufficient for a single parameter.
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 specific verb ('Get') with a clear resource ('business (listing)') and scope ('by its slug'). It distinguishes itself from sibling search tools by explicitly referencing search_businesses results, making the tool's unique role clear.
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 when-to-use guidance: 'Call this when the user asks for more information about a specific business.' It also indicates the prerequisite of using a slug from search_businesses, implying that search should be used first if no slug is available. However, it does not explicitly exclude other alternatives or mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_business_categoriesList Business CategoriesAReturns all industry categories and their business types with IDs. Use the business type IDs in search_businesses (businessTypeIds) to filter listings by category. Call this first when you need to discover which IDs to use for a given industry or business type.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false. The description adds that this is a discovery tool returning IDs for use in search_businesses, but does not detail response format or size; still, for a zero-param read-only list, this is sufficient context.
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, front-loaded with the primary function, followed by usage guidance. No redundant words.
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 no-parameter, read-only tool with no output schema, the description covers what it does, when to use it, and how to use the result, making it complete in context.
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?
There are zero parameters, so the description need not explain parameter semantics. It adds meaning about the output (categories and business types with IDs), which is 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?
The description clearly states 'Returns all industry categories and their business types with IDs', specifying a unique resource and its output, distinguishing it from siblings like list_languages and search_businesses.
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 explicitly instructs to use business type IDs in search_businesses (businessTypeIds) and says to call this first for discovering IDs, providing clear when-to-use guidance and the downstream consumer tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_languagesList LanguagesAReturns all languages with their IDs. Use these IDs in search_brokers (languageIds) to find brokers who speak specific languages. Call this when you need to discover which language IDs to use.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns 'all languages' (scope) and includes IDs, but does not detail the response structure, ordering, or any potential limitations. While adequate for such a simple tool, it adds limited behavioral context beyond 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 two sentences long, front-loads the primary function, and provides usage context in the second sentence. Every word contributes value, with no redundancy or fluff.
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 reference-list tool with strong annotations, the description is complete. It states what is returned (all languages with IDs) and how to use the result (search_brokers languageIds), which fully addresses the agent's needs given the lack of parameters and output schema.
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?
There are zero parameters, and the schema coverage is trivially 100%. Baseline for no-parameter tools is 4. The description adds no parameter details because none are needed, which is appropriate.
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 function with a specific verb ('Returns') and resource ('all languages with their IDs'). It also distinguishes itself from sibling tools that focus on search or contact operations, making its purpose unmistakable.
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 explicitly explains when to use this tool ('Call this when you need to discover which language IDs to use') and how the output integrates with another tool ('Use these IDs in search_brokers (languageIds)'). This provides strong usage guidance and alternative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_brokersSearch BrokersASearch for business brokers (agents) on Venturu by location, name, languages, and more. Returns verified brokers with email and phone redacted.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| name | No | ||
| page | No | ||
| sort | No | ||
| limit | No | ||
| state | No | ||
| county | No | ||
| zipCode | No | ||
| countryCode | No | ||
| languageIds | No | ||
| neighborhood | No | ||
| opportunityScore | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral details: results are 'verified brokers' and 'email and phone redacted.' This goes beyond the annotations by informing the agent about output content and data policy.
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 two sentences, front-loaded with the primary action ('Search for business brokers'), and each sentence earns its place by conveying purpose and key output characteristics. No redundant 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?
Given the tool has 12 parameters and no output schema, the description provides a high-level overview but omits pagination/sorting behavior and details on the return structure beyond redaction. However, the core functionality is clear, and annotations cover safety aspects, making this reasonably complete for a search 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?
Schema description coverage is 0%, so the description must compensate. It mentions 'location', 'name', and 'languages', which loosely maps to city/state/county/zipCode/neighborhood/countryCode, name, and languageIds. However, it does not explain page, limit, sort, or opportunityScore, leaving these ambiguous. The description covers the main search facets but not all parameter semantics.
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 purpose: searching for business brokers (agents) on Venturu with specific filters (location, name, languages). It also notes the return includes verified brokers with redacted contact info, distinguishing it from similar tools like 'search_businesses' and 'get_broker'.
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 usage context—use this tool when you need to search for brokers—but does not explicitly mention when to use alternatives or provide exclusions. Sibling tools are present but not referenced. This is clear context without explicit alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_businessesSearch BusinessesASearch for businesses (listings) for sale on Venturu. Supports natural-language location (e.g. 'Palm Beach, FL', 'Miami', '33101') via the location parameter, or an exact bbox. Use flat min/max fields for ranges (e.g. minPrice/maxPrice, minRevenue/maxRevenue, minProfit/maxProfit, minSde/maxSde, minOpportunityScore/maxOpportunityScore). Returns censored listing data with titles and addresses handled according to listing visibility settings.
| Name | Required | Description | Default |
|---|---|---|---|
| bbox | No | ||
| limit | No | ||
| state | No | ||
| cursor | No | ||
| maxSde | No | ||
| minSde | No | ||
| listedBy | No | ||
| location | No | ||
| maxPrice | No | ||
| minPrice | No | ||
| statuses | No | ||
| maxProfit | No | ||
| minProfit | No | ||
| saleTypes | No | ||
| maxRevenue | No | ||
| minRevenue | No | ||
| visaQualified | No | ||
| maxDownPayment | No | ||
| maxSdeMultiple | No | ||
| minDownPayment | No | ||
| minSdeMultiple | No | ||
| businessTypeIds | No | ||
| orderByProperty | No | recommended | |
| sbaPrequalified | No | ||
| maxEmployeeCount | No | ||
| minEmployeeCount | No | ||
| orderByDirection | No | desc | |
| propertyIncluded | No | ||
| maxRevenueMultiple | No | ||
| minRevenueMultiple | No | ||
| maxEstablishmentAge | No | ||
| maxOpportunityScore | No | ||
| maxOwnerWorkedHours | No | ||
| minEstablishmentAge | No | ||
| minOpportunityScore | No | ||
| minOwnerWorkedHours | No | ||
| buyerFinancingAvailable | No | ||
| includeMissingMultiples | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral context beyond annotations by noting 'Returns censored listing data with titles and addresses handled according to listing visibility settings,' which discloses output censorship and visibility behavior not present in 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 three sentences long, front-loaded with the core purpose, and every sentence adds value. 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?
The description covers location, ranges, and return censorship, but given the tool has 38 parameters, nested objects, and no output schema, it omits guidance on pagination (cursor/limit), ordering (orderByProperty/orderByDirection), and the overall result shape. For a complex search tool, this is a moderate gap, so a score of 3 is appropriate.
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?
With 0% schema description coverage, the description compensates by explaining the most complex parameters: location (natural-language vs bbox) and the min/max range pattern with concrete examples (minPrice/maxPrice, minRevenue/maxRevenue, etc.). It does not explain all 38 parameters, but many are self-explanatory from their names, and the description adds meaningful guidance for the trickier ones.
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 purpose: 'Search for businesses (listings) for sale on Venturu.' It uses a specific verb ('search') and resource ('businesses/listings'), and distinguishes from siblings like search_brokers and get_business by naming the platform and resource type.
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 usage context for parameters, such as 'Supports natural-language location ... or an exact bbox' and 'Use flat min/max fields for ranges.' However, it does not explicitly mention when to use this tool versus alternatives (e.g., get_business for a single listing, search_brokers for brokers), so there's no explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
who_am_iWho am IAReturns the identity of the currently authenticated user. Requires authentication. Use this to verify that the connection is correctly authenticated (e.g. in the voice agent).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only/non-destructive. The description adds that authentication is required and that the tool returns identity info, which provides useful behavioral 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?
Two sentences, front-loaded with the core purpose, followed by a usage hint. Every word earns its place; no fluff.
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-param, read-only tool with no output schema, the description covers what it returns, the auth requirement, and a concrete use case. Nothing essential 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 has zero parameters, and schema coverage is 100% (no properties). No parameter explanation is needed; the baseline 4 applies as the description still notes the auth prerequisite.
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 states a specific action ('Returns the identity of the currently authenticated user') with a clear resource. It is distinct from all sibling tools, which focus on brokers, businesses, categories, languages, and searches.
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?
Explicitly says to use it for verifying authentication, e.g., in a voice agent. This provides clear context for when to invoke this tool and distinguishes it from data-fetching siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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Control your server's listing on Glama, including description and metadata
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