JobOracle Job Market Intelligence MCP
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Average 2.8/5 across 8 of 8 tools scored.
Most tools have distinct purposes, but job_search and remote_jobs could overlap in functionality for remote job searches, potentially causing confusion. The other tools like company_jobs, job_compare, job_trends, and salary_insights are clearly differentiated by their specific focuses on company-specific listings, market comparisons, trend analysis, and salary data, respectively.
Tool names follow a consistent snake_case pattern throughout, such as company_jobs and job_search, which aids readability. However, there is a minor deviation with health_check, which uses a different verb style (health instead of job-related terms), though it still fits the overall naming convention.
With 8 tools, the count is well-scoped for a job market analysis server, covering key areas like job searching, company insights, trends, and salary data. Each tool appears to serve a specific, useful function without redundancy, making the set manageable and comprehensive for the domain.
The tool surface covers core job market operations, including search, comparison, trends, and salary insights, with no major gaps. However, there might be minor omissions, such as tools for detailed job application processes or user-specific job tracking, but these are not essential for the server's apparent purpose of market analysis and insights.
company_jobsCInspectAll open positions at a specific company.
| Name | Required | Description | Default |
|---|---|---|---|
| company | Yes | Company name | |
| country | No | de | |
| results_per_page | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It provides no behavioral details such as pagination, default country filtering, or response structure, reducing transparency.
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 redundant words. However, it is so brief that it sacrifices necessary detail, making it less helpful despite its efficiency.
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 absence of output schema and annotations, the description should explain more about result behavior and parameter effects. It fails to do so, leaving a simple but under-specified tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'specific company' which aligns with the required 'company' parameter, but it does not address 'country' or 'results_per_page'. With only 33% schema coverage, this gap is not compensated.
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 identifies the resource as open positions and the scope as a specific company, which distinguishes it from broader job search tools. However, it lacks an explicit verb like 'list' or 'get', making it slightly less directive.
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 phrase 'at a specific company' implies the tool is for company-specific job lookups, giving some context. But it does not explicitly state when to use this over sibling tools like job_search or provide any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkCInspectServer status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. 'Server status' does not explain whether the operation is read-only, what side effects (if any) exist, error handling, or response format. It is completely silent on behavior.
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 under-specified to the point of being a fragment rather than a useful sentence. While short, it omits essential details and is not structured to convey critical 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 no output schema and no annotations, the description must explain what 'server status' means, what the expected response is, and how to interpret it. It does none of these, leaving the agent with insufficient information.
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 explicitly shows an empty object, so the description need not explain any parameters. The baseline of 4 applies because the schema already covers everything.
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 'Server status' is essentially a restatement of the tool name 'health_check' without specifying an action or resource detail. It gives no verb and fails to clarify the exact purpose or return value, though it does distinguish from unrelated job-search siblings.
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?
No guidance is provided on when to use this tool versus alternatives, such as job_alerts_check or job_search. The description does not mention context, prerequisites, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
job_alerts_checkAInspectHow many new jobs posted today/3 days/week for a query. Quick market pulse.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Keywords | |
| country | No | de | |
| location | No | City or region |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the core behavior (returns counts for different time windows) but does not mention whether results are estimates, how data is sourced, or any limitations. It is adequate but not rich.
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 short sentences with no filler. The main purpose is front-loaded, and the 'quick market pulse' tag is an efficient summary. Every word 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?
For a simple counting tool with no output schema, the description covers the essential behavior and time frames. It lacks details on return format or error conditions, but given the low complexity and modest schema, it is 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?
Schema description coverage is 67%, with query and location described. The description adds relevance by tying query to the counting purpose, but it does not clarify the country parameter or how time periods are derived (there is no explicit time parameter). The description adds modest value 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 indicates the tool counts new job postings for a query over time periods (today/3 days/week), distinguishing it from siblings like job_search and job_trends. However, it lacks an explicit verb like 'get' or 'count', making the purpose slightly indirect.
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 phrase 'Quick market pulse' implies using this tool for a fast high-level check of job posting volume, but it does not explicitly state when to prefer it over similar siblings like job_trends or job_search. No exclusionary guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
job_compareAInspectCompare job markets across cities for a role: job count and salaries.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Job title | |
| country | No | de | |
| locations | Yes | List of cities to compare |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear the full burden of behavioral disclosure. It only states the core action and outputs, but omits critical behavior details such as whether the operation is read-only, how salaries are aggregated (e.g., median vs average), potential limitations, or response format. This is insufficient for a tool with zero annotation support.
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, well-structured sentence of 12 words. It is front-loaded with the verb 'Compare', states the scope ('across cities for a role'), and specifies the outputs. Every phrase adds value with zero 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?
The tool is simple, but with no output schema and no annotations, the description is somewhat sparse. It tells the user the tool compares job count and salaries, but does not clarify the return structure (e.g., per city breakdown), the default country behavior, or any prerequisites. This is adequate but not fully 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 descriptions cover 2 of 3 parameters (query and locations, both adequately described). The tool-level description reinforces these mappings (role → query, cities → locations) but adds no new meaning. The 'country' parameter is undocumented in both schema and description; given 67% coverage, the description should have compensated for this gap but does not.
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 'Compare' and clearly defines the resource: 'job markets across cities for a role', with explicit outputs 'job count and salaries'. This differentiates it from sibling tools like job_search (single search) and salary_insights (salaries only), 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 provides clear context: use this tool when you need to compare job markets across multiple cities for a specific role. However, it does not explicitly state exclusions or name alternative tools, so it stops short of a perfect 5 but is still clearly actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
job_searchBInspectSearch jobs by title, skill, location. Filter by type and recency.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number (starts at 1) | |
| query | Yes | Job title or keywords, e.g. 'Business Development Manager' | |
| country | No | Country code: de, gb, us, at, ch, nl, fr, it, pl, br, au, in | de |
| sort_by | No | Sort: relevance, date, salary | relevance |
| location | No | City or region, e.g. 'Bielefeld' or 'Berlin' | |
| full_time | No | Full-time only | |
| salary_min | No | Minimum annual salary filter | |
| max_days_old | No | Only jobs posted within N days | |
| results_per_page | No | Results per page (max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'Search jobs' and 'Filter by type and recency', giving minimal behavioral disclosure. It does not mention whether the operation is read-only, pagination behavior, response format, or any side effects.
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 sentence, front-loaded with the verb and resource, and contains no filler. Every word contributes to the core purpose.
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 9 parameters and no output schema, the description is minimal but not entirely inadequate. It covers the search dimensions and mentions filtering, but it omits context such as the supported countries, sorting options, pagination, and result limits, which are present in the schema. The tool is a straightforward search, so the description meets a baseline completeness.
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 each parameter including a description in the schema, so the baseline is 3. The description adds a high-level summary like 'title, skill, location' and 'type and recency', which maps to parameters (query, location, full_time, max_days_old), but it does not add meaning beyond what the schema already states.
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 ('Search') and resource ('jobs'), with clarifying dimensions (title, skill, location). It distinguishes general job search functionality from siblings like company_jobs and remote_jobs, though it does not explicitly say 'for general job search, not company-specific or remote-only'.
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?
No guidance is provided on when to use this tool versus alternatives. Sibling tools like remote_jobs or company_jobs are not mentioned, and there are no exclusions or context cues for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
job_trendsCInspectTop companies hiring for a field. Rising demand signals.
| Name | Required | Description | Default |
|---|---|---|---|
| field | Yes | Field or job category, e.g. 'Vertrieb' or 'IT' | |
| country | No | de |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden, but it only hints at output (top companies, rising demand) without disclosing output format, pagination, or any side effects. This is insufficient for a data-returning 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?
While there is no wasted prose, the description is under-specified—two fragments do not constitute a well-structured explanation. It is more indicative of missing content than efficient writing.
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 tool with no output schema and many siblings, the description is far too sparse. It lacks return format, usage context, and any clarification of 'rising demand signals,' making it incomplete for reliable selection and invocation.
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 50% (field documented, country not). The description adds no parameter details, failing to compensate for the undocumented 'country' parameter. It only repeats the concept of 'field' from 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 communicates the core purpose: showing top companies hiring for a field and rising demand signals. It is distinct from sibling tools like job_search and company_jobs, though it lacks an explicit verb and reads more like a phrase than a clear statement.
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?
No guidance is provided on when to use this tool versus alternatives like salary_insights or job_search. The description does not mention any exclusions or preferred contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remote_jobsCInspectFind remote-only positions for a role or skill.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Keywords | |
| country | No | de | |
| results_per_page | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It simply states 'find' which implies a read operation, but it doesn't disclose any behavioral traits such as output format, pagination, country-specific behavior, or any limitations. The description is too sparse to provide meaningful transparency.
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, well-structured sentence with no unnecessary words. It front-loads the core purpose effectively. However, its brevity borders on under-specification, but the structure itself is clean and efficient.
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 three parameters, no output schema, and no annotations, the description should provide more context. It doesn't explain what the returned data looks like, how the country parameter affects results, or how the tool relates to sibling search tools. The description is incomplete 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?
Schema coverage is only 33%, with only 'query' having a description. The description adds context for the query (role or skill) but provides no insight into 'country' or 'results_per_page', leaving their purpose ambiguous. Given the low schema coverage, the description fails to compensate.
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 'find' and a clear resource 'remote-only positions', and further specifies the target is 'for a role or skill'. It distinguishes itself from sibling tools by focusing on remote-only positions, though it doesn't explicitly contrast with job_search or others.
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?
No guidance is provided on when to use this tool versus alternatives like job_search or company_jobs. There are no mentions of exclusions, prerequisites, or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
salary_insightsCInspectSalary ranges for a role in a location.
| Name | Required | Description | Default |
|---|---|---|---|
| role | Yes | Job title, e.g. 'Sales Manager' | |
| country | No | de | |
| location | No | City or region |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavior, but it merely states 'Salary ranges' with no detail on return format, data source, or how location/country affect results. It doesn't mention whether it returns a single range or multiple data points, nor any defaults or side effects.
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 brief and front-loaded, which is positive, but it borders on under-specification. It could be more informative while remaining concise.
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?
No output schema or annotations exist, and the tool has three parameters, so the description should clarify return values and behavior. It fails to explain what format the salary ranges come in or how the country/location filter is applied, leaving it incomplete for an agent to invoke confidently.
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 already describes 'role' and 'location,' but the description adds no additional parameter context. The 'country' parameter is not documented in the description, leaving its semantics only inferable from the default value 'de.'
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 the tool provides salary ranges for a role and location, but uses a noun phrase rather than an explicit action verb like 'retrieve' or 'get.' It clearly distinguishes from sibling job-search tools by focusing on salary, but lacks a specific verb-value structure.
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?
There is no guidance on when to use this tool vs alternatives like job_search or job_trends. The description only defines what it contains, with no mention of preferred use cases or exclusions.
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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