US Import Records Buyer Finder MCP Server
Click on "Deploy 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., "@US Import Records Buyer Finder MCP ServerFind US importers with pickleball in their name that shipped this year"
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.
US Import Records Buyer Finder MCP Server
An MCP server for the Mamba Labs US Import Records Buyer Finder actor on Apify. Find US importers and their overseas suppliers from customs records.
What's Inside
Related MCP server: mcp-hts
What it does
Search company names and get one row per US importer or overseas supplier, with shipment counts and last shipment dates. Ask for profiles to add trading partners, HS codes, product descriptions, and recent shipments, up to 20 a run.
All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.
Quick start
You need Node.js 18 or newer and an Apify account with an API token.
Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:
{
"mcpServers": {
"mamba-us-import-records-buyer-finder": {
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-us-import-records-buyer-finder"
],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Restart the client. The find_us_importers tool appears.
Prerequisites
Node.js 18 or newer.
An Apify API token from console.apify.com/account/integrations, set as
APIFY_TOKEN. The server lists its tool without a token; a call needs one.
Example prompts
"Find US importers with pickleball in their name that shipped this year."
"Who supplies Pickleball Central, and from which countries?"
"Which overseas suppliers named Zhejiang ship the most to the US?"
Tool
find_us_importers. One tool. Example arguments:
{
"search": [
"pickleball"
],
"max_results": 20
}Inputs
Every buyer facing input of the actor. Omitted inputs take the actor's own defaults.
Input | Type | Required | Description |
| array | no | Company name words, for example pickleball or walmart. The site matches company names, not what a company imports. Up to 50 terms. |
| array | no | ImportYeti company or supplier links to read in full, up to 20 a run. |
| string | no | importers: US companies importing. suppliers: overseas companies shipping to the US. both: either. |
| string | no | Optional, YYYY-MM-DD. Drops companies whose last shipment is older. |
| number | no | Optional. Drops companies with fewer shipments in total. |
| number | no | Up to 1000. Default 100. The site served about 140 rows per term in testing, so a broad term can stop sooner. |
| boolean | no | true adds trading partners, their countries, HS codes, product descriptions, and recent shipments to the first rows, up to Maximum profiles. Priced as a profile row. |
| number | no | Up to 20, because the site limits page views per address and this actor stops there. Each profile adds about 7 seconds. |
| string | no | Optional. The run stops before a charge that would pass this amount. Summary rows are always returned. |
Pricing
Pay per event on Apify, billed to your Apify account. Prices in USD.
Event | Free plan | Bronze | Silver | Gold |
| $0.0025 | $0.002375 | $0.00225 | $0.002125 |
| $0.008 | $0.0076 | $0.0072 | $0.0068 |
| $0.002 | $0.002 | $0.002 | $0.002 |
Summary rows, refused input, filtered rows, and refused pages are free. Mamba Labs pays the platform costs of the run, Apify proxy traffic included.
Full actor documentation
apify.com/mambalabs/us-import-records-buyer-finder
License
MIT. See LICENSE.
Available Tools
1 toolfind_us_importersFind US importers and suppliersARead-onlyIdempotent
Search US customs bill of lading records by company name for importers and overseas suppliers. Returns shipment counts and last shipment dates. Set include_profiles to add trading partners, HS codes, product descriptions, and recent shipments, up to 20 a run. The search matches company names, not products.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | importers: US companies importing. suppliers: overseas companies shipping to the US. both: either. | |
| search | No | Company name words, for example pickleball or walmart. The site matches company names, not what a company imports. Up to 50 terms. | |
| date_from | No | Optional, YYYY-MM-DD. Drops companies whose last shipment is older. | |
| max_results | No | Up to 1000. Default 100. The site served about 140 rows per term in testing, so a broad term can stop sooner. | |
| company_urls | No | ImportYeti company or supplier links to read in full, up to 20 a run. | |
| max_profiles | No | Up to 20, because the site limits page views per address and this actor stops there. Each profile adds about 7 seconds. | |
| min_shipments | No | Optional. Drops companies with fewer shipments in total. | |
| max_charge_usd | No | Optional. The run stops before a charge that would pass this amount. Summary rows are always returned. | |
| include_profiles | No | true adds trading partners, their countries, HS codes, product descriptions, and recent shipments to the first rows, up to Maximum profiles. Priced as a profile row. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the returned fields, the expansion triggered by include_profiles, and the 20-profile ceiling per run. It stops short of disclosing cost or credit consumption, which lives only in the max_charge_usd parameter description.
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?
Four sentences, front-loaded with purpose and return shape, with no wasted phrasing. The 'matches company names, not products' caveat is valuable but sits after the include_profiles sentence, which slightly interrupts the flow from search behavior to output options.
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?
With nine parameters, no output schema, and no siblings, the description carries real weight and it does cover return values, the search matching rule, and the profile expansion cap. It leaves the company_urls full-read mode and the charge-limiting behavior to the schema, which is a minor gap for a tool with this much surface area.
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%, so all nine parameters are already documented in the schema, setting the baseline at 3. The description reinforces two of them (search term semantics and include_profiles expansion) but adds no syntax, format, or default information beyond what the schema already states.
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 definition names a specific verb and resource, 'Search US customs bill of lading records by company name,' and states the result shape, 'shipment counts and last shipment dates.' An agent knows exactly what data it retrieves and the importers/suppliers dual scope is clear from the description plus the mode enum.
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 gives a clear use context and one explicit exclusion: 'The search matches company names, not products,' plus 'Set include_profiles to add...' which tells the agent when to turn that flag on. There are no sibling tools to route between, so the only missing piece is guidance on when this tool is not appropriate at all.
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
v1.0.0- First observed
find_us_importers
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of misselection between competing tools. Its description also explicitly bounds its behavior (company-name search, not product search), leaving no ambiguous overlap.
The single tool follows a clear verb_noun snake_case pattern (find_us_importers) that would scale predictably if more tools were added. No mixed conventions exist.
One tool is thin for a data-lookup service, even a narrow one; it is saved by an include_profiles parameter that bundles partner, HS code, and shipment data into the same call. The surface is borderline minimal rather than clearly well-scoped.
Importer lookup by company name is covered, but the description explicitly excludes product search, and profile expansion is capped at 20 records per run with no detail-retrieval or pagination tool. Agents will hit dead ends whenever they need product-based discovery or bulk results.
Maintenance
Related MCP Connectors
Global customs trade data and company registry. Search shipments, and look up legal entities.
U.S. tariffs (HTS), Schedule B codes, export statistics, party screening and FMC license checks.
Search USITC tariff schedules, inspect heading trees, and look up published duty rates.
US HTS search, origin-specific duty breakdowns, tariff sources and missing-fact guidance.
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