Allows discovering companies currently hiring for specified role keywords and locations by searching public Greenhouse job boards.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Company Discovery List Builder MCP Server Find companies hiring remote data engineers."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server for the Mamba Labs Company Discovery List Builder actor on Apify.
Market in, companies out. Give it role keywords and a location and it returns the companies currently hiring for that. A second mode returns US SEC filers whose filings contain your phrase. No paid data source is involved.
npx -y @mambalabsdev/mcp-company-discovery-list-builder{
"mcpServers": {
"mamba-company-discovery-list-builder": {
"command": "npx",
"args": ["-y", "@mambalabsdev/mcp-company-discovery-list-builder"],
"env": { "APIFY_TOKEN": "your-apify-token" }
}
}
}Get an Apify token at console.apify.com/account/integrations.
Related MCP server: AI Tooling Detector MCP Server
build_company_listMarket in, companies out. Give it role keywords and a location and it returns the companies currently hiring for that. A second mode returns US SEC filers whose filings contain your phrase. No paid data source is involved.
Input | Type | Required | Notes |
| enum | yes | hiring returns companies currently hiring for your role keywords, built from a live index of public Greenhouse and Ashby job boards. filings returns US SEC filers whose filings contain your phrase. |
| string | no | Comma separated. Matched as whole words against live job titles, so account executive matches Enterprise Account Executive and does not match Executive Assistant. Leave empty to match any role. Used in hiring mode. |
| string | no | Exact phrase searched in SEC filings, for example agentic AI. Used in filings mode. |
| string | no | Comma separated SEC form types, for example 10-K,10-Q. Used in filings mode. |
| string | no | Substring match against the job location string, for example London, Remote, New York. Locations are free text on every job board, so this is a plain substring test: Remote does not match US Remote. |
| string | no | Skip companies with fewer open roles than this. A rough size proxy. Sent as a string so it works from Clay. |
| string | no | How many companies to return, 1 to 2000. Sent as a string so it works from Clay. You are billed per company returned, not per company examined. |
| boolean | no | Look up each company's website. Off by default: it adds roughly a second per company and about two thirds of companies resolve. Check domain_status and domain_confidence before trusting a result. |
| boolean | no | Force a fresh Common Crawl enumeration instead of the cached one. The cached universe is rebuilt about monthly on its own, so leave this off unless you need the newest crawl. |
You are charged per company returned, not per company examined, plus a small actor start fee. max_companies is therefore a hard cost cap.
Pricing is on the actor's Apify page. Running this server consumes Apify credits.
It is a thin client for the Apify actor. It passes your input through and returns the actor's output unchanged. Every behavior described above lives in the actor, not here.
Errors are surfaced, never swallowed. An invalid input, an invalid token, an exhausted balance, a timeout, or a run that returns anything other than a dataset all come back as an explicit tool error rather than as an empty result.
The actor is on the Apify Store. This wrapper is MIT licensed.
Built by Mamba Labs
Build a list of companies from a market definition, in two modes. hiring returns companies currently advertising for your role keywords, built from a live index of public Greenhouse and Ashby job boards; role_keywords are matched as whole words against live job titles, so account executive matches Enterprise Account Executive and does not match Executive Assistant. filings returns US public companies whose SEC filings of the form types you name contain your exact phrase. location_contains is a plain substring test against the job board's own free text location string, so Remote does not match US Remote. min_open_jobs is a rough size proxy. resolve_domains looks up each company's website, which adds roughly a second per company and resolves about two thirds of the time, so check domain_status and domain_confidence before trusting a domain. The underlying company universe is rebuilt about monthly on its own; refresh_universe forces a fresh enumeration and is rarely what you want. You are billed per company returned, not per company examined, so max_companies is the cost dial. Requires an APIFY_TOKEN and consumes Apify credits. Read only.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | hiring returns companies currently hiring for your role keywords, built from a live index of public Greenhouse and Ashby job boards. filings returns US SEC filers whose filings contain your phrase. | |
| filing_forms | No | Comma separated SEC form types, for example 10-K,10-Q. Used in filings mode. Default: "10-K". | |
| filing_phrase | No | Exact phrase searched in SEC filings, for example agentic AI. Used in filings mode. | |
| max_companies | No | How many companies to return, 1 to 2000. Sent as a string so it works from Clay. You are billed per company returned, not per company examined. Default: "100". | |
| min_open_jobs | No | Skip companies with fewer open roles than this. A rough size proxy. Sent as a string so it works from Clay. Default: "1". | |
| role_keywords | No | Comma separated. Matched as whole words against live job titles, so account executive matches Enterprise Account Executive and does not match Executive Assistant. Leave empty to match any role. Used in hiring mode. | |
| resolve_domains | No | Look up each company's website. Off by default: it adds roughly a second per company and about two thirds of companies resolve. Check domain_status and domain_confidence before trusting a result. Default: true. | |
| refresh_universe | No | Force a fresh Common Crawl enumeration instead of the cached one. The cached universe is rebuilt about monthly on its own, so leave this off unless you need the newest crawl. Default: false. | |
| location_contains | No | Substring match against the job location string, for example London, Remote, New York. Locations are free text on every job board, so this is a plain substring test: Remote does not match US Remote. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses latency and success rates for resolve_domains, matching behavior (whole-word vs substring), the monthly universe rebuild, per-company billing, and the need to check domain_status/domain_confidence. This is extensive and adds significant value without contradicting 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 a dense single paragraph but is front-loaded with the core purpose and each sentence provides useful detail. However, it could be more scannable with bullet points or short sections given its length, earning a 4 rather than 5.
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?
There is no output schema, so the description carries the burden of explaining return values. It mentions domain_status and domain_confidence, but does not outline the overall result structure (e.g., company fields). For such a configurable tool, this is a notable gap, though the core use cases and side effects are well documented.
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?
Although the schema already covers all parameters (100% coverage), the description enriches several: role_keywords gets concrete examples of whole-word matching, location_contains explains the substring test with a counterexample, resolve_domains notes time and success rate, and max_companies is framed as a cost dial. This exceeds the baseline 3 for high 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 opens with 'Build a list of companies from a market definition, in two modes,' which clearly states the verb, resource, and scope. It explicitly names the two modes (hiring, filings) and details what each returns, effectively distinguishing the tool's behavior without needing sibling comparisons.
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?
It provides concrete guidance on when to use each mode: hiring for live job boards, filings for SEC filings. It also warns against using refresh_universe ('rarely what you want'), explains billing implications of max_companies, and notes token/credit requirements—clear context for usage and parameter selection.
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. Dates show when Glama detected each change.
v1.0.0build_company_listWith only a single tool in the server, there is no possibility of confusing it with another. The tool's description clearly distinguishes its internal modes and parameters, so an agent can unambiguously invoke the correct operation.
The sole tool name 'build_company_list' follows a standard verb_noun pattern, which is predictable and clear. Since there are no other tools to compare conventions, consistency is maximized.
The server exposes only one tool, which feels thin compared to typical MCP servers with 3-15 tools. However, the tool is highly configurable and covers the entire scope of building a company list, so the count is borderline but not severely deficient.
The single tool effectively covers the full lifecycle of the server's purpose: it builds company lists from two distinct sources, supports domain resolution, and has a refresh mechanism. The domain is narrowly defined, and no obvious operations are missing for achieving the stated goal.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Run Signal Lab Apify Actors for price tracking, keywords, RAG, transcripts, Reddit, jobs, and menus.
Find companies hiring for a role and geo, qualify them, and watch them for changes.
Verified, long-tail company search: describe what you want, get an LLM-verified company shortlist.
Search job postings, companies, and technology stacks across 10M+ companies.
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