Jobs Base
Server Details
Search builder roles - jobs where one person owns engineering, product, and QA end-to-end.
- 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 4.5/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose with no overlap: get_job retrieves details for a specific job, list_filters provides available filter values, and search_jobs searches job listings with filters. The descriptions explicitly differentiate their roles, eliminating any ambiguity.
All tool names follow a consistent verb_noun pattern (get_job, list_filters, search_jobs) using snake_case. The naming is predictable and readable, with no deviations in style or convention.
With 3 tools, the count is slightly low but reasonable for the server's focused scope on job searching and filtering. It covers core operations (search, get details, list filters), though additional tools like saving jobs or applying might be expected in a job board context.
The tool set covers the essential workflow for job searching: discover filters, search listings, and get details. Minor gaps exist, such as no update/delete operations for user-specific actions (e.g., saving jobs), but the core domain of job discovery is well-covered without dead ends.
Available Tools
3 toolsget_jobARead-onlyInspect
Get full details of a specific builder job by its ID, including description, skills, experience requirements, benefits, and company info. Use this after search_jobs to retrieve the complete listing.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The job ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, indicating this is a safe read operation with deterministic results. The description adds valuable context about what data is returned (specific fields like benefits and company info) and the typical workflow pattern, which goes beyond what annotations provide.
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 zero waste - the first sentence states purpose and scope, the second provides clear usage guidance. Every word serves a specific function, and the information is front-loaded with the most important details first.
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 operation with good annotations, the description provides appropriate context about what data is returned and how it fits into the workflow. While there's no output schema, the description enumerates the key return fields, making it reasonably complete for this 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 description coverage is 100%, with the single parameter 'id' already documented as 'The job ID' in the schema. The description doesn't add any additional parameter semantics beyond what the schema provides, but the baseline is appropriate given complete schema 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 specific action ('Get full details') and resource ('builder job by its ID'), listing the exact data returned (description, skills, experience requirements, benefits, company info). It explicitly distinguishes from sibling 'search_jobs' by specifying this is for retrieving complete listings after 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?
The description provides explicit guidance on when to use this tool ('after search_jobs to retrieve the complete listing'), creating a clear workflow relationship with the sibling tool. It effectively tells the agent to use search_jobs first, then this tool for detailed information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_filtersARead-onlyInspect
Get available filter values for search_jobs: job types, workplace types, cities, countries, seniority levels, and companies. Call this first to discover valid filter values before searching, especially for country codes and available cities.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only and closed-world behavior, which the description aligns with by describing a data retrieval operation. The description adds value beyond annotations by specifying the types of filter values returned and the recommendation to call it first for discovery, enhancing context without contradicting 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 front-loaded with the core purpose in the first sentence, followed by actionable guidance. Every sentence earns its place by providing essential information without redundancy, resulting in a compact and well-structured 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 complexity (simple retrieval with no parameters), annotations covering safety, and no output schema, the description is largely complete. It explains what the tool does, when to use it, and what data it provides, though it could briefly mention the return format or data structure for full 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?
With 0 parameters and 100% schema description coverage, the baseline is 4 as per the rules. The description compensates by explaining the semantic purpose of the tool (to retrieve filter values for search_jobs), which adds meaning beyond the empty input schema, making it clear why no parameters are needed.
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 with specific verbs ('Get available filter values') and resources ('job types, workplace types, cities, countries, seniority levels, and companies'), and distinguishes it from sibling tools by explicitly mentioning 'search_jobs' as the related operation. It goes beyond a tautology by detailing what types of filter values are retrieved.
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 explicit guidance on when to use this tool ('Call this first to discover valid filter values before searching') and why ('especially for country codes and available cities'), and implicitly suggests alternatives by referencing 'search_jobs' as the subsequent step. It clearly defines the tool's role in the workflow.
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 and filter builder job listings on jobsbase.io — a curated board exclusively for "builder" roles (cross-functional positions where one person owns engineering, product, and delivery end-to-end: founding engineers, solo builders, 0-to-1 roles). Every job here is already an AI-native builder role, so do NOT search for generic terms like "builder", "AI", "full-stack", or "engineer" — they are redundant and will hurt results. Just use filters (country, workplace, seniority, etc.) to narrow down. Use q only for specific technologies, companies, or domain keywords. All parameters are optional.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Optional keyword for specific technologies, domains, or companies (e.g. "React", "fintech", "Stripe"). Do NOT use generic terms like "builder", "AI", "engineer", or "developer" — every job on this board already matches those. Omit to browse all jobs. | |
| city | No | Filter by city. Comma-separated for multiple: London,Berlin | |
| sort | No | Sort order: relevance (best match first), posted_at (newest first, default), salary (highest salary first) | |
| type | No | Filter by job type. Comma-separated for multiple: full-time,contract. Values: full-time, part-time, contract, freelance, internship | |
| limit | No | Results per page (default 30, max 100) | |
| state | No | Filter by state/province name. Comma-separated for multiple: California,Texas | |
| cursor | No | Cursor for next page of results | |
| region | No | Filter by geographic region. Comma-separated for multiple. Values: north_america, latin_america, europe, asia_pacific, middle_east_africa | |
| company | No | Filter by exact company name | |
| country | No | Filter by country code. Comma-separated for multiple: US,GB,CA | |
| workplace | No | Filter by workplace. Comma-separated for multiple: remote,hybrid. Values: remote, hybrid, on-site | |
| posted_within | No | Filter by posting date: past 24h, 3d, 7d, 14d, or 30d | |
| salary_at_most | No | Show jobs that can pay at most this amount annually (normalized to annual equivalent) | |
| education_level | No | Filter by minimum education level | |
| salary_at_least | No | Show jobs that can pay at least this amount annually (normalized to annual equivalent) | |
| seniority_level | No | Filter by seniority. Comma-separated for multiple: mid,senior. Values: internship, entry, mid, senior, lead, executive | |
| visa_sponsorship | No | Set to true to only show jobs that offer visa sponsorship | |
| experience_no_more_than | No | Show jobs requiring no more than this many years of experience |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, covering safety and scope. The description adds valuable behavioral context: it explains that all jobs are AI-native builder roles, warns against redundant search terms that hurt results, and clarifies that all parameters are optional. No contradiction with 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?
Well-structured and front-loaded with essential information. Every sentence earns its place: defines the resource, explains specialization, gives critical usage warnings, and provides parameter guidance. No wasted words while maintaining clarity.
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 search tool with 18 parameters, 100% schema coverage, and read-only annotations, the description provides excellent context about the specialized domain and usage patterns. The main gap is lack of output schema information (what results look like), but given the annotations and parameter documentation, it's mostly 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 100%, so the schema already documents all 18 parameters thoroughly. The description adds some semantic context by explaining the board's specialization affects how to use the 'q' parameter, but doesn't provide additional parameter details beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
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 specific action ('search and filter') and resource ('builder job listings on jobsbase.io'), with explicit differentiation from sibling tools by specifying this is for curated builder roles only. It distinguishes from generic search tools by explaining the specialized nature of the job board.
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?
Provides explicit guidance on when to use this tool vs. alternatives: 'do NOT search for generic terms' and 'use filters to narrow down.' It gives clear context about the board's specialization and offers practical advice on parameter usage, distinguishing it from generic job search tools.
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.
Discussions
No comments yet. Be the first to start the discussion!