JobsPipe
Server Details
Live job postings for AI agents: search normalized postings from 30+ ATS feeds and job boards by title, skill, country, remote, seniority and recency. Also lists sources and pricing plans.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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.
Tool Definition Quality
Average 3.8/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: listing job sources, listing pricing plans, searching all jobs, and searching Upwork jobs specifically. No overlap in functionality.
All tools follow a consistent verb_noun pattern in snake_case (list_job_sources, list_pricing_plans, search_jobs, search_upwork_jobs).
4 tools is appropriate for a server focused on job search and metadata. The scope is narrow, and each tool serves a necessary function without bloat.
The tool set covers listing sources, pricing, and searching, but lacks tools for retrieving individual job details or managing queries. The search_jobs tool only returns API guidance, not results, which is a notable gap.
Available Tools
4 toolslist_job_sourcesARead-onlyInspect
List the ATS and job-board sources JobsPipe normalizes into a single JSON schema, with coverage and freshness notes.
| Name | Required | Description | Default |
|---|---|---|---|
| name_contains | No | Optional case-insensitive substring to filter sources by name (e.g. "workday"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive behavior. The description adds that output includes coverage and freshness notes, providing useful 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?
Single sentence, front-loaded with verb and resource, no wasted words. Efficiently conveys 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?
Given a simple listing tool with one optional filter and annotations present, the description adequately covers what the tool does and the nature of its output. Could mention pagination or limits, but not necessary for this level of 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 description coverage is 100% for the single parameter, which has a clear description. The tool description does not add additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists ATS and job-board sources normalized into a single JSON schema, with coverage and freshness notes. Verb 'list' plus specific resource distinguishes it from sibling tools that handle pricing or searching.
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 explicit guidance on when to use this tool versus siblings. The purpose is implied by name and description, but no when-not-to or alternatives are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_pricing_plansARead-onlyInspect
List JobsPipe pricing plans with monthly price in USD, request quota and included features.
| Name | Required | Description | Default |
|---|---|---|---|
| plan | No | Optional plan name to return just one plan (e.g. "free", "builder", "scale"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, making the safe, read-only nature clear. The description adds that it returns specific fields but does not disclose any additional behavioral traits, such as default behavior or output format.
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 of 12 words, efficiently conveying the tool's purpose. Every word is meaningful with no wasted text.
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's simplicity (1 optional param, no output schema), the description covers the key aspects: what it lists and what information is returned. It could mention that by default all plans are listed, but this is implied.
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% (the single optional parameter 'plan' is described with examples). The description adds no extra parameter details beyond what the schema provides, meeting the baseline for high 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 uses a specific verb 'List' with a clear resource 'JobsPipe pricing plans' and specifies the return fields (monthly price, request quota, features). This clearly distinguishes it from sibling tools like list_job_sources which lists job sources.
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 does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. However, the purpose is simple enough that usage is implied: call this when you need pricing plan information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsARead-onlyInspect
Search live, normalized job postings across 30+ sources by title, skill/tech, country, remote, seniority, employment type and recency. Returns guidance for calling the authenticated REST API that runs the query.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum rows to return. | |
| remote | No | Only remote roles when true. | |
| job_title_or | No | Match any of these job titles. | |
| description_or | No | Match any of these skills or technologies in the posting. | |
| job_seniority_or | No | Match any of these seniority levels. | |
| employment_type_or | No | Match any of these employment types. | |
| job_country_code_or | No | Match any of these ISO 3166-1 alpha-2 country codes. | |
| posted_at_max_age_days | No | Only postings published within this many days. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true (safe read) and openWorldHint=true (dynamic results). The description adds important context: it 'returns guidance for calling the authenticated REST API', implying the tool does not directly return jobs but provides instructions. This clarifies the tool's behavior 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: first sentence efficiently lists capabilities, second sentence clarifies output. No wasted words, front-loaded with 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?
Given the tool has 8 optional parameters and no output schema, the description covers the filtering options well. However, it does not explain what 'normalized' means or detail the 'guidance' return format, leaving some uncertainty about the tool's output.
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% (all 8 parameters are described in the schema). The description enumerates the filter dimensions, confirming but not adding meaning beyond the schema. 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 searches 'live, normalized job postings across 30+ sources' and lists specific filter dimensions (title, skill/tech, country, remote, seniority, employment type, recency). This distinguishes it from sibling 'search_upwork_jobs', which is a specialized search for Upwork.
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 effectively communicates the scope of the tool (multi-source job search) and implies it should be used over 'search_upwork_jobs' when broader coverage is needed. However, it lacks explicit guidance on when not to use it or specific prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_upwork_jobsBRead-onlyInspect
Search live Upwork job postings ingested by JobsPipe. Returns normalized rows with budget, skills and client signals.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | ||
| limit | No | Maximum rows to return (1-200, default 25). | |
| order | No | ||
| offset | No | Pagination offset. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's mention of returning normalized rows adds some value but does not deeply disclose behavior like rate limits, data freshness, or potential unexpected results despite the openWorldHint.
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 with no wasted words. The first sentence front-loads the core action and resource, and the second adds useful output context.
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 exists, so the description partially compensates by naming output fields. However, it lacks explanation of parameter usage and pagination details, leaving some gaps for a tool with 4 parameters.
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 only 50% schema description coverage (limit and offset have descriptions), the description does not compensate by explaining the 'sort' or 'order' parameters, missing an opportunity to clarify their meaning beyond the enum values.
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 Upwork job postings', and adds context about the data source (JobsPipe) and output fields (budget, skills, client signals), which helps differentiate from sibling tools like '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?
No guidance is provided on when to use this tool versus alternatives such as 'search_jobs'. There is no mention of prerequisites, exclusions, or preferred use cases.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
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