Search real, recent job postings from company career pages and ATS boards, scored for fit.
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap. The single tool's purpose is clearly stated and self-contained.
The tool name 'search_jobs' follows a clear verb_noun convention. With only one tool, naming is trivially consistent and intuitive.
A single tool feels thin for a server, though it is acceptable for a narrowly scoped job-search utility. It sits at the borderline, but the focused purpose justifies its existence.
The server covers the core job-search operation effectively, returning rich results with links. Minor gaps exist (e.g., no separate detail or filtering tool), but agents can work around them via the provided URLs.
Find recent job postings that match target job titles in given locations (or remote). Runs HuntBoard's own hunt: SQL narrowing over its index of company career pages and ATS boards, then an AI fit score. Returns up to max_results jobs scored 7-10 with title, company, location, link, source and a one-line reason.
| Name | Required | Description | Default |
|---|---|---|---|
| titles | Yes | Target job titles, e.g. ["Backend Engineer", "Platform Engineer"]. Parentheticals are stripped and head phrases matched. | |
| locations | No | Cities, regions or countries, e.g. ["Tel Aviv", "Israel"]. Optional only when remote_ok is true. | |
| remote_ok | No | Also include remote roles open to the given locations (or global remote roles). | |
| max_results | No | How many jobs to return, 1-50. | |
| exclude_titles | No | Title fragments to drop, e.g. ["Manager", "QA"]. | |
| exclude_locations | No | Location fragments to drop. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context beyond those hints: it reveals the internal pipeline ('SQL narrowing over its index of company career pages and ATS boards, then an AI fit score'), the scoring threshold for returned results (7-10), and the return fields. This lets the agent predict that results are pre-vetted, non-deterministic, and sourced externally—useful information not present in 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 with zero fluff. The main action is front-loaded, followed by a compact explanation of the internal method and the return shape. Every clause contributes either purpose, behavioral transparency, or output details, making it appropriately sized and scannable.
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?
Without an output schema, the description compensates by listing the return fields explicitly (title, company, location, link, source, one-line reason) and the cap via max_results. The main gaps are undefined 'recent' time window and no mention of empty-result or error behavior. For a read-only search tool with rich annotations, these are minor omissions, so the definition is strong but not fully exhaustive.
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 fully documents all six parameters, including defaults, limits, and examples. The description adds no parameter-specific semantics beyond what is already in the schema; it merely echoes the title/location/remote concept. A baseline 3 is appropriate when the schema carries 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 opens with a precise verb-resource statement: 'Find recent job postings that match target job titles in given locations (or remote)'. It specifies the filters (titles, locations, remote) and the result set, so an agent immediately knows what this tool does and what it does not do. No sibling tools exist to confuse it, and the purpose is unambiguous.
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 are no sibling tools, so no alternative-routing guidance is needed. The description gives clear contextual usage signals: it runs an AI-scored hunt over company career pages and ATS boards and returns only jobs scored 7-10, which tells the agent this is the tool for high-quality, pre-filtered job matches. It stops short of explicit 'use when / do not use when' guidance, so it earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
search_jobsSearch a live index of millions of open jobs from employer career sites and 100+ ATS platforms.
Read job postings live from employer career sites across 10 applicant tracking systems.
Semantic search over 3.5M+ live US job postings pulled straight from company ATSes. Read-only.
Search 690k open jobs from official ATS feeds, and what changed since your last check.
Add one secure layer between your agents and this server.
