recruiter-roles-mcp
Server Details
Search Recruiter Roles: live recruiter jobs, companies, sectors, locations, and market stats.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
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Tool Definition Quality
Average 4.4/5 across 7 of 7 tools scored.
Each tool has a distinct purpose: fetching individual entities (get_company, get_job), listing directories (list_companies, list_locations, list_sectors), aggregate data (market_stats), and searching (search_jobs). No overlap.
All tool names follow a consistent verb_noun pattern with underscores (e.g., get_company, list_companies). No camelCase or mixing of conventions.
With 7 tools, the set is well-scoped for a job browsing service. Each tool provides essential functionality without unnecessary duplication or bloat.
The tool set covers the core use cases: fetching detailed job and company info, browsing by location/sector, searching with filters, and market overview. No obvious gaps for a read-only job board.
Available Tools
7 toolsget_companyGet company profileARead-onlyIdempotentInspect
Fetch a single company's full profile plus a paginated list of its active jobs.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page of the company's jobs. Default: 1. | |
| slug | Yes | The company slug (e.g. 'robert-half'). | |
| per_page | No | Jobs per page. Default: 20, max: 100. |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds value by specifying that it returns a company profile and a paginated list of active jobs, providing behavioral context beyond annotations. No contradictions.
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, concise sentence of 17 words. It is front-loaded with the verb and resource, and every word contributes meaning without 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?
Given the tool has 3 parameters, full schema coverage, and an output schema (not shown but present), the description adequately conveys the tool's purpose and behavior. An agent can understand what the tool does without needing additional 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?
Schema description coverage is 100%, so the baseline is 3. The description does not add new meaning beyond the schema; it reinforces that pagination parameters relate to jobs, but that is already clear from the schema descriptions.
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 that the tool fetches a single company's full profile along with a paginated list of its active jobs. The verb 'Fetch' is specific, the resource is well-defined, and it distinguishes itself from siblings like 'list_companies' (which lists companies) and 'get_job' (which gets a single job).
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 for retrieving a specific company's profile and jobs, but does not explicitly state when to use it versus alternatives or provide exclusions. The context is clear enough for an agent to infer, but lacks explicit guidance that would earn a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_jobGet job detailARead-onlyIdempotentInspect
Fetch the full detail for a single job by its slug, including the complete description, requirements, benefits, tech stack, and apply contact.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The job slug (the last path segment of its URL, or the 'slug' field from search_jobs). |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds the behavioral context that it fetches 'full detail' including specific sections. It does not disclose potential rate limits or authentication requirements, which are already covered by 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 concise sentence with no extraneous information. It front-loads the main action and result, and every element adds value.
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, the description sufficiently covers purpose and parameter semantics. An output schema exists, so the description need not detail return values. Could be improved by adding a note about when to use this tool over search_jobs, but overall it is adequate.
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 only parameter 'slug' has 100% schema description coverage. The description adds valuable semantic context: 'the last path segment of its URL, or the slug field from search_jobs', helping the agent derive the correct value. This goes beyond the schema's basic description.
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 verb 'Fetch' and the resource 'full detail for a single job by its slug', listing specific fields (description, requirements, benefits, tech stack, apply contact). It implicitly distinguishes from search_jobs (which returns multiple jobs) and other sibling 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 implies usage for retrieving a single job's full details given a slug. It does not explicitly state when not to use or name alternatives, but the context of sibling tools and the specific fetch purpose makes the usage reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_companiesList recruiting companiesARead-onlyIdempotentInspect
Browse the directory of recruiting companies and agencies with their active job counts. Filter by name, company type, or HQ country.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Search company name. | |
| page | No | Page number. Default: 1. | |
| sort | No | Sort order. Default: job_count. | |
| country | No | HQ country code (e.g. 'US', 'GB'). | |
| per_page | No | Results per page. Default: 20, max: 100. | |
| company_type | No | Company type filter. |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| meta | Yes | |
| response_generated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds that it returns 'active job counts', a useful behavioral detail 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?
Single sentence, front-loaded with purpose, no extraneous words. Every part adds value.
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 rich schema (6 params, all described) and existing annotations, description is complete enough for a 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?
Schema coverage is 100% so baseline is 3. Description lists three filter types but doesn't add significant meaning beyond schema descriptions.
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 uses specific verb 'Browse' and resource 'recruiting companies and agencies' with 'active job counts'. Clearly distinguishes from siblings like get_company (single) and search_jobs (jobs).
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?
States when to use: browsing/filtering directory. Implies context but lacks explicit when-not-to-use or alternative guidance, though siblings are known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_locationsList locationsARead-onlyIdempotentInspect
List the location hierarchy (countries, regions, or cities) with active job counts. Use the returned codes/slugs for the 'state' and 'city' filters in search_jobs.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | Hierarchy level to return. Default: countries. | |
| region | No | Filter cities by region code (e.g. 'TX'). Use with level=cities. | |
| country | No | Filter by country code (e.g. 'US', 'GB'). |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| response_generated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnly, idempotent, non-destructive hints. Description adds that it returns job counts and codes/slugs, useful 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?
Two concise sentences with no fluff, front-loaded with purpose and usage guidance.
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 output schema exists, description is complete with clear purpose, parameters, and usage context. No missing elements.
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 covers all parameters (100% coverage). Description adds context like default level and how region works with level=cities, providing marginal extra value.
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 location hierarchy (countries, regions, cities) with active job counts, using specific verbs and resource, and distinguishes from sibling tools like list_companies.
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 tells when to use: to obtain codes/slugs for filters in search_jobs. No when-not, but clear context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sectorsList sectorsARead-onlyIdempotentInspect
List all recruiting sectors with their current active job counts. Use the returned slugs for the 'sector' filter in search_jobs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| response_generated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about returning 'current active job counts' and slugs, extending beyond annotations without contradicting them.
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: first states purpose, second provides usage context. Every sentence earns its place, no wasted 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?
Given no parameters, presence of output schema, and rich annotations, the description fully covers purpose and downstream use. No gaps identified.
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 with 100% schema coverage. Per guidelines, baseline score for 0 parameters is 4. Description adds no parameter info, 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 'List all recruiting sectors with their current active job counts.' It specifies a distinct verb (list) and resource (sectors with job counts), differentiating it from siblings like list_companies or search_jobs.
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 instructs 'Use the returned slugs for the 'sector' filter in search_jobs,' providing clear downstream usage. It does not mention when not to use or alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
market_statsRecruiter job market statsARead-onlyIdempotentInspect
Aggregate market overview: total active jobs, posting velocity (24h / 7d), and breakdowns by sector, employment type, work arrangement, and country.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| response_generated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true and destructiveHint false. The description adds value by specifying the exact aggregate data returned (posting velocity, breakdowns), complementing the safety profile with behavioral details.
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?
One sentence concisely captures all key information: purpose, scope, and breakdowns. No wasted 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?
Given zero parameters, annotations, and an output schema (as indicated by context signals), the description is complete. It specifies all relevant output categories.
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 zero parameters, the schema already handles parameter documentation. The description does not need to add parameter semantics, and it effectively describes the output 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 clearly states the tool provides an 'aggregate market overview' with specific metrics (total active jobs, posting velocity, breakdowns). It distinguishes itself from sibling tools like get_company or search_jobs by focusing on market-level stats.
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 for obtaining market-level statistics, but does not explicitly state when to use this tool versus siblings like list_sectors. It provides clear context but no alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsSearch recruiter jobsARead-onlyIdempotentInspect
Search live recruiter and talent-acquisition job listings on Recruiter Roles. Supports full-text search and filtering by sector, location, employment type, work arrangement, salary, and recency. Returns a paginated list with salary, company, location, and a tracked apply URL.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Full-text search across job title and company name. | |
| city | No | City slug, comma-separated (e.g. 'dallas-tx'). | |
| page | No | Page number. Default: 1. | |
| sort | No | Sort order. Default: recent. | |
| state | No | State/region code, comma-separated (e.g. 'TX,NY,BC'). Use list_locations for codes. | |
| sector | No | Sector slug, comma-separated for multiple (e.g. 'technology,financial-services'). Use list_sectors for valid slugs. | |
| per_page | No | Results per page. Default: 20, max: 100. | |
| is_remote | No | Shorthand for work_arrangement=remote. | |
| salary_min | No | Minimum salary in USD. Only returns jobs with a disclosed salary at or above this. | |
| source_type | No | 'direct' = employer-posted, 'scraped' = aggregated. | |
| posted_since | No | ISO date — jobs posted on or after this date. | |
| updated_since | No | ISO datetime — for incremental sync; jobs updated on or after this. | |
| employment_type | No | Employment type filter. | |
| salary_disclosed | No | true = only jobs with a disclosed salary; false = only undisclosed. | |
| work_arrangement | No | Work arrangement filter. |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| meta | Yes | |
| response_generated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that the tool returns a paginated list with specific fields (salary, company, location, tracked apply URL), which is helpful 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?
The description is two sentences long, front-loaded with the core purpose, and every word adds value. It is efficient and free of 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?
Given the complexity (15 parameters, 4 enums, output schema exists), the description covers the essential behavioral aspects: pagination, filter types, and output fields. It does not mention error handling or rate limits, but for an idempotent read-only search tool, this is adequate.
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?
All 15 parameters have descriptions in the input schema (100% coverage). The description adds value by summarizing the categories of filters (sector, location, employment type, work arrangement, salary, recency) and the returned fields, which helps the agent understand the overall semantics without reading each 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 clearly specifies the verb 'Search' and the resource 'live recruiter and talent-acquisition job listings on Recruiter Roles'. It distinguishes this tool from sibling tools such as get_company, get_job, and list_* by emphasizing full-text search and multiple filters.
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 states that the tool supports full-text search and filtering by various criteria, which implies its use case. It does not explicitly mention when not to use it or alternatives, but the sibling list provides enough context for an agent to differentiate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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