mcp-job-board-keyword-signal-scanner
This server scans a company's job board for open roles matching specific categories or custom keywords, returning structured hiring signal data ready for use in CRMs, Clay, or AI workflows.
Scan job boards by domain: Provide a company domain (e.g.,
stripe.com) and the server searches for open roles across major ATS platforms including Greenhouse, Lever, Ashby, Workday, and Rippling.Filter by role categories: Choose from predefined categories — GTM, Engineering, Finance, Operations, Executive — or use custom keywords for targeted role matching.
Custom keyword scanning: Supply your own keyword arrays (e.g.,
machine learning,platform) for highly specific role matching.Enable fallback search: Optionally fall back to a pre-indexed job database if no live ATS results are found.
Track changes over time: Pass in previous run data to compute newly added or removed roles compared to a prior scan.
Assess hiring signal strength: Output includes a
hiring_signalboolean and asignal_strengthscore (high/medium/low) to gauge a company's hiring activity.Get flat, Clay-ready JSON output: Results include matched role counts and titles per category, detected ATS platform, top matched role, and most recent posting date — compatible with Clay, CRMs, or AI agent workflows.
Scans Greenhouse job boards for open roles matching specified categories and custom keywords.
Job Board Keyword Signal Scanner MCP Server
An MCP server that scans a company's job board for the roles you care about. It wraps the Mamba Labs Job Board Keyword Signal Scanner actor on Apify and returns a Clay-ready flat JSON row to any MCP client.
What's Inside
Related MCP server: mcp-gtm-suite
What it does
Give it a company domain and a set of role categories, and it scans Greenhouse, Lever, Ashby, Workday, and Rippling for matching open roles. Pick from GTM, Engineering, Finance, Operations, Executive, or pass your own custom keywords. You get back a flat row of matched role counts and titles per category, ready for Clay, a CRM, or an AI agent workflow. All of the scanning runs on Apify. This package is a thin client that calls the actor and hands back the result.
Quick start
You need Node.js 18 or newer and an Apify account with an API token.
Add this to your Claude Desktop config:
{
"mcpServers": {
"mamba-job-board-scanner": {
"command": "npx",
"args": ["-y", "@mambalabsdev/mcp-job-board-keyword-signal-scanner"],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Get your token at https://console.apify.com/account/integrations, paste it in, and restart Claude Desktop. The scan_job_board_keywords tool will be available.
Prerequisites
Node.js 18 or newer
An Apify account with an API token
Example prompts
"Is stripe.com hiring engineers? Scan their job board for Engineering roles."
"Check openai.com for GTM and Executive openings."
"Scan figma.com for Finance and Operations roles."
"Look for roles matching 'machine learning' and 'platform' at datadoghq.com using custom keywords."
Inputs
company_domain(required): the bare company domain, nohttps://and no trailing slash. Example:stripe.comrole_categories(required): one or more of GTM, Engineering, Finance, Operations, Executive, Marketing, HR, CustomerSuccess, Data, Product, Legal, Design, or Custom. Matching is case insensitive and ignores separators, socustomer_successandCustomer Successboth work, andsalesresolves to GTM.custom_keywords(optional): keyword strings to match when Custom is included.enable_fallback(optional): fall back to a pre-indexed job database when the live ATS cascade finds nothing.previous_roles_detectedandprevious_run_date(optional): pass a prior run's results to compute newly added or removed roles over time.
Output
The tool returns the actor's flat JSON row for the scanned company, including matched role counts and titles per requested category, the ATS platform detected, and optional change tracking. See the Apify Store page for the full output schema.
Example output
{
"company_domain": "figma.com",
"hiring_signal": true,
"ats_platform": "greenhouse",
"categories_searched": [
"Engineering"
],
"matched_role_count": 8,
"signal_strength": "high",
"top_matched_role": "Staff Engineer",
"most_recent_posting_date": "2026-05-27",
"run_date": "2026-05-28"
}Features
Configurable role categories: GTM, Engineering, Finance, Operations, Executive, Custom
User-defined keyword arrays for custom scanning
Per-category counts via roles_by_category, with category-level signal scoring
Same ATS cascade as the Hiring Signal Scraper
Full actor documentation
This server is a thin client and holds no scanning logic. For the complete input and output reference, pricing, and run history, see the Apify Store page:
https://apify.com/mambalabs/job-board-keyword-signal-scanner
Mamba Labs GTM Suite
This server is part of the Mamba Labs GTM Suite, a fleet of twelve specialized MCP servers for go-to-market signal intelligence, each backed by a dedicated Apify actor.
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Built by Mamba Labs | npm | Apify Store
License
MIT
Built by Mamba Labs. https://apify.com/mambalabs
Available Tools
1 toolscan_job_board_keywordsScan Job Board KeywordsARead-onlyIdempotent
Scan a company's job board for roles in chosen categories across Greenhouse, Lever, Ashby, Workday, and Rippling. Pick from GTM, Engineering, Finance, Operations, Executive, or supply custom keywords. Returns a flat, Clay-ready JSON row of matched role counts and titles per category. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.
| Name | Required | Description | Default |
|---|---|---|---|
| company_domain | Yes | Bare company domain without https:// and without a trailing slash. Example: stripe.com | |
| role_categories | Yes | One or more role categories to scan for. Valid values: GTM, Engineering, Finance, Operations, Executive, Custom. Use Custom together with custom_keywords. | |
| custom_keywords | No | Keyword strings to match when Custom is included in role_categories. Required only if Custom is requested. | |
| enable_fallback | No | If true, falls back to a pre-indexed job database when the live ATS cascade finds nothing. | |
| previous_roles_detected | No | Comma-separated matched role titles from a previous run, used to compute newly added or removed roles. | |
| previous_run_date | No | ISO date of the previous run, e.g. 2026-03-15. Used for tracking changes over time. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds 'Read-only; requires an APIFY_TOKEN and consumes Apify credits per call' beyond the annotations (readOnlyHint=true). This provides critical behavioral and cost information.
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?
Three sentences front-load the key purpose, then output format, then requirements. Every sentence adds value with no 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?
Description covers return type, cost, and required token. Without output schema, it sufficiently explains outputs. Minor omission: no details on error cases, but acceptable given 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%, so baseline is 3. The description adds minimal extra meaning since schema already explains parameter choices; no compensation 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?
Description clearly states verb 'scan', resource 'job board', and specific ATS platforms (Greenhouse, Lever, etc.), distinguishing it from any potential siblings. It also mentions the output format.
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?
Description explicitly lists role categories to pick from and explains when to use custom keywords. While no sibling tools exist to provide usage alternatives, it gives clear guidance on usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.3- First observed
scan_job_board_keywords
TDQS
Scored across 1 tool
Only one tool exists, so there is no ambiguity with other tools. The tool's purpose is clearly defined.
The single tool name 'scan_job_board_keywords' follows a clear verb_noun pattern, which is consistent and descriptive.
The server has exactly one tool, which is appropriate for its focused purpose of scanning job boards for keyword signals. A single, well-defined tool is sufficient for this narrow scope.
The tool covers the full intended functionality: scanning multiple ATS platforms with configurable categories and returning results. No additional tools are necessary for its read-only scanning purpose.
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