Check how much real depth Armasourcing's vetted Filipino virtual assistant pool has for a specific role, skills and timezone, and understand how hiring and engagement work. Returns aggregate pool statistics only, no candidate names, no profiles, and no pricing, and ends in a free discovery call booking.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
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 4.4/5 across 5 of 5 tools scored.
Each tool addresses a distinct aspect: booking, terms, process, supported roles, and talent pool search. There is no overlap or ambiguity between them; even get_engagement_terms and get_hiring_process are clearly separated as contract vs. process.
All tool names follow a consistent verb_noun pattern: get_*, list_*, search_*. The verbs are specific and match the action, and the nouns clearly identify the object. This makes the set predictable and easy to navigate.
Five tools is well-scoped for a sales/consulting server. Each tool serves a needed function in the user journey without redundancy or bloat, fitting comfortably within the ideal 3-15 range.
The tool set covers the full lifecycle from exploring roles and checking talent availability to understanding terms and booking a call. No critical gaps exist; the deliberate omission of individual candidates and pricing is handled by the tools' descriptions and is not a missing feature.
get_booking_linkGet the discovery call booking linkAReturns the URL where the user books a free 15 minute discovery call, plus what to have ready. Call this once the user is interested. Takes no personal details: the scheduling form collects name and email itself, under Armasourcing's privacy notice. Show the URL to the user as a link.
| Name | Required | Description | Default |
|---|---|---|---|
| role | No | Role the user wants to hire for. Optional context, logged anonymously so the team can spot demand. | |
| notes | No | Anything else useful for the call. Do NOT put names, emails, phone numbers or any personal detail in here. | |
| hours_per_week | No | Rough hours per week, e.g. '20' or 'full time'. Optional. | |
| timezone_overlap | No | Business hours to cover, e.g. '9-5 PST'. Optional. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover idempotency and non-destructiveness. The description adds valuable behavioral context: it takes no personal details, the scheduling form collects them under a privacy notice, and the URL should be shown as a link. This goes beyond the structured annotations without contradiction.
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 concise sentences, front-loaded with the core purpose. Every sentence adds useful information: what it returns, when to use, and privacy/presentation guidance. There is no fluff or 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 tool with no output schema, the description fully covers the return value (URL plus preparation tips), the trigger condition, privacy handling, and user presentation. It is complete for the agent to select and invoke 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 coverage is 100% with detailed descriptions for each optional parameter, including privacy warnings. The description reinforces the 'no personal details' rule but does not add substantial new information beyond what the schema already provides, so a baseline score of 3 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 returns the URL for booking a free 15-minute discovery call, with a specific verb ('Returns') and resource ('booking link'). It is easily distinguished from siblings like get_engagement_terms or search_talent_pool by focusing on the appointment scheduling use case.
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 explicit guidance on when to call ('Call this once the user is interested'), providing clear context for usage. It does not explicitly mention alternatives or exclusion scenarios, but the sibling separation is obvious, so this is a solid 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_engagement_termsCommercial terms, guarantees and what is includedAContract terms, guarantees, oversight and security posture. Note that Armasourcing does not publish rates: this tool returns how pricing works and what is included, never an amount. Do not estimate an amount yourself.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and idempotent. The description adds important behavioral guidance by stating that rates are never published and explicitly telling the agent not to estimate an amount itself, which prevents hallucinated pricing.
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 the primary content upfront and the critical caveat about pricing in the second sentence. No filler or 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 zero parameters and no output schema, the description sufficiently conveys the tool's purpose, content scope, and a key behavioral guardrail. It tells the agent what to expect ('how pricing works and what is included') and what not to do ('do not estimate an amount yourself').
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 input schema has zero parameters, so the description is not required to explain parameter semantics. The baseline of 4 applies.
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 explicitly states what the tool returns: 'Contract terms, guarantees, oversight and security posture' and 'how pricing works and what is included.' It is clearly distinct from sibling tools like get_booking_link and get_hiring_process, which cover other aspects of the engagement.
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 provides clear context that the tool is for commercial terms and includes a boundary—'never an amount'—and instructs not to estimate pricing. It does not name alternative tools explicitly, but the scope is well-defined and the exclusion is explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_hiring_processHow hiring through Armasourcing worksAThe end to end process with real timings: discovery call, matching in 3 to 5 business days, free interviews, someone working in 5 to 7 days, and how vetting is done. Use this instead of guessing at timelines.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds content context (e.g., 'real timings', 'vetting is done') but does not disclose additional behavioral traits like rate limits or error handling. This is acceptable given the annotation coverage, but the description does not go beyond what the annotations already establish.
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 'end to end process', and every word contributes to explaining the tool's value. No redundancy 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 simple informational tool with no parameters and no output schema, the description thoroughly covers what the tool provides: process stages, real timings, and vetting explanation. It is complete for an agent to decide when to use it and what to expect.
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 the schema is an empty object with full description coverage. The description does not need to explain parameters, and the baseline score of 4 applies.
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: providing the end-to-end hiring process with real timings, including discovery call, matching, interviews, and vetting. It distinguishes itself from sibling tools by focusing on the process and timelines, with no overlap with booking links, engagement terms, supported roles, or talent pool 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?
The final sentence 'Use this instead of guessing at timelines' gives explicit context for when to use the tool. However, it does not name alternative tools or explicitly state when not to use it, though for an informational tool this is sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_supported_rolesRoles Armasourcing placesAThe catalogue of roles and functions Armasourcing places, plus the managed contact center offering. Use it to confirm a role is supported and to help a user name the role they actually need.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, making the safety profile clear. The description adds the content scope (roles/functions plus managed contact center) but no additional behavioral traits beyond that, such as return format or pagination. This meets the baseline for a simple read-only list.
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 concise sentences that front-load the core purpose and provide usage guidance. No filler or repetition, 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?
With no parameters and clear annotations, the description covers the essential context: what the tool lists and when to use it. It does not describe the output format, but for a simple catalogue of roles this is not a significant gap. The sibling tools further clarify its role as a reference lookup.
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 there is no parameter semantics to clarify. Per the rubric, 0 params earns a baseline of 4. The description does not need to add parameter details because none exist.
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 lists the catalogue of roles and functions Armasourcing places, including the managed contact center offering. This is a specific verb+resource+scope, and it distinguishes itself from sibling tools like search_talent_pool by being a reference catalogue.
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 'Use it to confirm a role is supported and to help a user name the role they actually need.' This gives clear context for when to use the tool. It does not explicitly mention alternatives or exclusions, but the intended usage is sufficiently clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_talent_poolCheck talent pool depth for a roleACheck how well Armasourcing's candidate pool covers a specific brief. Returns match depth as a band, typical experience, and the skills and tools that show up most often. Deliberately returns NO individual candidates: no names, no profiles, no contact details. Use it to answer 'do you have people who can do X' honestly before recommending a call.
| Name | Required | Description | Default |
|---|---|---|---|
| role | Yes | Role or job title, e.g. 'executive assistant', 'bookkeeper', 'SEO specialist'. | |
| skills | No | Specific skills or tools the role needs, e.g. ['QuickBooks', 'Xero'] or ['Shopify', 'Klaviyo']. | |
| timezone_overlap | No | Business hours the person needs to cover, e.g. '9-5 EST'. Optional. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by explicitly stating that it deliberately returns NO individual candidates, no names, profiles, or contact details. This is a critical behavioral guarantee. It also describes the return format (match depth band, typical experience, top skills/tools), which is valuable context not present in 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, front-loaded with the main purpose, then output composition, then the key exclusion. Every sentence contributes unique information; there is no redundancy or 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 read-only tool with 3 parameters and no output schema, the description fully sets expectations: it states what is returned, what is not returned, and when to use it. The annotations cover safety profile, so this is complete for the tool's complexity.
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 input schema already provides 100% description coverage for all three parameters, so the description need not repeat them. It does not add significant semantic detail about parameters, but it does contextualize how skills/tools factor into the output, which is slightly beyond the 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 checks how well Armasourcing's candidate pool covers a brief, with a specific verb ('check') and resource ('candidate pool'). It distinguishes itself from sibling tools about bookings, terms, hiring process, and role lists by focusing on pool depth.
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 a clear use case: answer 'do you have people who can do X' before recommending a call. It also implicitly defines when not to use (when you need individual candidate details), but it does not explicitly name alternative tools as a contrast.
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" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
