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US Government Data

Name: US Government Data
Author: CBLU2005

by CBLU2005

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

us-govdata-mcp

MCP-Server für US-Regierungsdaten — durchsuchen Sie Baugenehmigungen, Bundesvertragsmöglichkeiten (SAM.gov) und das nationale Gesundheitsdienstleisterverzeichnis (NPI/NPPES) von Claude, Cursor oder jedem Model Context Protocol-Client.

CBLU2005/us-govdata-mcp MCP server

License: MIT Node >= 18

Alle drei Datenquellen sind offizielle Regierungsveröffentlichungen (städtische Open-Data-Portale, der öffentliche Auszug von SAM.gov, die CMS NPPES API) — kein HTML-Scraping, keine Anmeldungen, keine fragilen Selektoren. Die schwere Arbeit wird von drei produktiven Apify-Actoren erledigt, die auf Ihrem eigenen Apify-Konto laufen.

Testen Sie es in 30 Sekunden — kein Konto, keine Kosten

Bevor Sie entscheiden, ob dies einen API-Token wert ist, führen Sie es ohne einen aus:

{
  "mcpServers": {
    "us-govdata": {
      "command": "npx",
      "args": ["-y", "github:CBLU2005/us-govdata-mcp"],
      "env": { "APIFY_DRY_RUN": "1" }
    }
  }
}

Das ist die gesamte Einrichtung. Im Trockenlaufmodus gibt jedes Tool realistische Beispieldatensätze zurück plus die genaue Apify-API-Anfrage, die es gesendet hätte — so können Sie die tatsächliche Form der Daten sehen, bestätigen, dass Ihr Agent die Tools korrekt aufruft, und die Preisangaben in jeder Toolbeschreibung lesen, ohne ein Konto zu erstellen, einen Token einzufügen oder etwas auszugeben.

Fragen Sie Ihren Agenten etwas wie "finde Baugenehmigungen über 500.000 $, die diesen Monat in Austin ausgestellt wurden" und beobachten Sie den Tool-Aufruf von Anfang bis Ende. Wenn Sie Live-Daten wünschen, löschen Sie die Zeile APIFY_DRY_RUN und fügen Sie einen APIFY_TOKEN hinzu (siehe unten).

Related MCP server: PubRecords MCP

Tools

Tool	Was es durchsucht	Typische Filter	Preis*
`search_building_permits`	Baugenehmigungen von 10 offiziellen städtischen/kreiseigenen Open-Data-Quellen (NYC, Chicago, LA, Austin, SF, New Orleans, Baton Rouge, Montgomery Co. MD, Norfolk VA) — Genehmigungstyp, Status, Wert, Auftragnehmername/Lizenz	Städte, Ausstellungszeitraum, Genehmigungstyp, Volltext, Mindestwert	$0,005 / Datensatz
`search_federal_contract_opportunities`	Bundesweite RFPs, Aufforderungen, Quellensuche und Vergabebekanntmachungen von SAM.gov — mit E-Mails und Telefonnummern der Vertragsbeauftragten	Stichwort, NAICS, Bekanntmachungstyp, Vorbehalt (8A, WOSB, HUBZone...), Behörde, Bundesstaat, Daten	$0,004 / Datensatz
`search_healthcare_providers`	Das offizielle CMS-NPI-Register von über 8 Millionen US-Anbietern und Gesundheitsorganisationen — Fachgebiet, Lizenz, Praxis-Telefon/Fax, bevollmächtigte Personen	Fachgebiet, Bundesstaat, Stadt, PLZ (Platzhalter), Anbieter-/Organisationsname	$0,002 / Datensatz

* Ehrliche Preisangabe: Diese Tools verwenden kostenpflichtige, pro-Ergebnis abgerechnete Apify-Actoren, die von CBLU veröffentlicht werden. Ihr Apify-Konto wird nur für tatsächlich zurückgegebene Datensätze belastet — es gibt keine Abonnements oder Startgebühren. Jedes Tool gibt standardmäßig 25 Ergebnisse pro Aufruf zurück, sodass ein typischer Aufruf einen Bruchteil eines Cents kostet (25 Genehmigungen ≈ $0,13; 25 Vertragsbekanntmachungen ≈ $0,10; 25 Anbieter ≈ $0,05). Der kostenlose Plan von Apify enthält monatliches Plattformguthaben, das ausreicht, um diese Tools gelegentlich kostenlos zu nutzen. Actor-Seiten mit vollständigen Preisdetails:

Schnellstart

1. Apify-Token besorgen (kostenlos, ~2 Minuten)

Registrieren Sie sich unter https://console.apify.com/sign-up (der kostenlose Plan funktioniert).
Kopieren Sie Ihren API-Token von https://console.apify.com/settings/integrations.

Der Server startet und listet seine Tools ohne Token — der Token wird nur benötigt, wenn ein Tool tatsächlich aufgerufen wird.

2. Server zu Ihrem MCP-Client hinzufügen

Claude Desktop (claude_desktop_config.json → Einstellungen → Entwickler → Konfiguration bearbeiten):

{
  "mcpServers": {
    "us-govdata": {
      "command": "npx",
      "args": ["-y", "github:CBLU2005/us-govdata-mcp"],
      "env": {
        "APIFY_TOKEN": "your_apify_token_here"
      }
    }
  }
}

Claude Code:

claude mcp add us-govdata -e APIFY_TOKEN=your_apify_token_here -- npx -y github:CBLU2005/us-govdata-mcp

Cursor / Windsurf / andere MCP-Clients (gleiche Struktur wie Claude Desktop):

{
  "mcpServers": {
    "us-govdata": {
      "command": "npx",
      "args": ["-y", "github:CBLU2005/us-govdata-mcp"],
      "env": { "APIFY_TOKEN": "your_apify_token_here" }
    }
  }
}

Aus einem lokalen Klon:

git clone https://github.com/CBLU2005/us-govdata-mcp.git
cd us-govdata-mcp
npm install && npm run build
# then point your client at: node /path/to/us-govdata-mcp/dist/index.js

Docker:

docker build -t us-govdata-mcp .
docker run -i --rm -e APIFY_TOKEN=your_apify_token_here us-govdata-mcp        # stdio
docker run --rm -p 3000:3000 -e APIFY_TOKEN=... us-govdata-mcp --http 3000    # Streamable HTTP

3. Fragen Sie Ihren KI-Agenten Dinge wie

"Finde Baugenehmigungen für Neubauten über 500.000 $, die diesen Monat in Austin ausgestellt wurden, mit Auftragnehmernamen."
"Gibt es aktuelle Ausschreibungen für Cybersicherheit mit Kleinunternehmensvorbehalt, deren Antwortfrist nach heute liegt? Inklusive E-Mail des Vertragsbeauftragten."
"Liste Zahnärzte im Großraum Miami (PLZ 331) mit ihren Praxis-Telefonnummern auf."*

Transporte

stdio (Standard) — was Desktop-MCP-Clients verwenden: us-govdata-mcp
Streamable HTTP — zustandsloser Endpunkt unter POST /mcp, Gesundheitscheck unter GET /healthz: us-govdata-mcp --http 3000 (oder setzen Sie MCP_HTTP_PORT=3000)

Umgebungsvariablen

Variable	Erforderlich	Zweck
`APIFY_TOKEN`	Für Tool-Aufrufe	Ihr Apify-API-Token. Serverstart und Tool-Auflistung funktionieren ohne ihn; Tool-Aufrufe geben eine Einrichtungsanleitung zurück, bis er gesetzt ist.
`APIFY_DRY_RUN`	Nein	Auf `1` setzen, um vorgefertigte Beispieldatensätze ohne Netzwerkaufruf oder Kosten zurückzugeben — die Antwort enthält die genaue Apify-API-Anfrage, die gesendet worden wäre. Nützlich für Tests und CI.
`MCP_HTTP_PORT`	Nein	Starten Sie im Streamable-HTTP-Modus auf diesem Port anstelle von stdio.

So funktioniert es

Jedes Tool validiert seine Argumente (zod), erstellt die Actor-Eingabe und ruft den Endpunkt run-sync-get-dataset-items der Apify-API mit Ihrem Token über einen Authorization: Bearer-Header auf (niemals in der URL). Der Actor läuft auf der Apify-Plattform unter Ihrem Konto und die resultierenden Datensätze werden direkt als Tool-Ergebnis zurückgegeben. Dieser Server speichert keinen Zustand und sieht keine Daten außer der Durchleitung.

Entwicklung

npm install
npm test          # builds + runs the full smoke suite (introspection, tokenless
                  # error path, dry-run request construction, HTTP transport)

Die Testsuite benötigt kein Apify-Konto und kein Netzwerk — sie verwendet APIFY_DRY_RUN=1.

Lizenz

MIT © CBLU

Available Tools

3 tools

search_building_permitsSearch US building permitsA

Search recently issued US building permits from official city open-data portals (New York City, Chicago, Los Angeles, Austin, San Francisco, New Orleans, Baton Rouge, Montgomery County MD, Norfolk VA). Returns normalized permit records: permit number, type, work description, status, issue date, address, project valuation, and contractor name/license where published. Great for construction lead generation and market research. Runs the paid Apify actor https://apify.com/cblu/us-building-permits-scraper on YOUR Apify account (requires APIFY_TOKEN; pay per result: $0.005 per permit record ($5.00 / 1,000), charged only for records actually returned).

ParametersJSON Schema

Name	Required	Description
`cities`	No	Cities/counties to search. Use ["all"] or omit for every supported source. Each city is queried up to maxResultsPerCity.
`issuedAfter`	No	Only permits issued on/after this date (YYYY-MM-DD). Recommended — keeps results fresh and runs fast.
`searchQuery`	No	Full-text search across the source dataset, e.g. 'solar', 'pool', 'demolition', 'ADU'.
`issuedBefore`	No	Only permits issued on/before this date (YYYY-MM-DD).
`minValuation`	No	Only permits with declared project value >= this USD amount (permits without a published valuation are excluded when set).
`maxResultsPerCity`	No	Max permit records per selected city (1-2000, default 25). Each returned record is billed at $0.005 per permit record ($5.00 / 1,000).
`permitTypeContains`	No	Case-insensitive substring match on permit type / class / work type, e.g. 'electrical', 'roof', 'plumbing', 'new construction'.

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the tool runs on the user's Apify account requiring APIFY_TOKEN, pay-per-result pricing, and returns normalized permit records. Lacks details on error handling or rate limits but is transparent about costs and external dependence.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

4-sentence description, well-structured: purpose, returned fields, use case, technical details and pricing. Front-loaded with core purpose. The last sentence is dense with pricing details but remains understandable. Efficient for the information conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, supported cities, return fields, cost model, and authentication requirement. Lacks explanation of error handling if APIFY_TOKEN missing, and output structure is not described (no output schema). For 7 optional parameters and paid actor, the main gaps are minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already has descriptions for all 7 parameters (100% coverage). The description adds value by explaining the use case (lead generation) and cost implications (e.g., maxResultsPerCity billable). Also adds recommended usage hint for issuedAfter. Supplements schema with decision-relevant context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches US building permits from specific cities, specifies normalized fields returned, and distinguishes from sibling tools which cover federal contracts and healthcare providers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context for construction lead generation and market research, and mentions the paid Apify actor with pricing. Does not explicitly state when not to use or compare to alternatives, but sibling tools are clearly different.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_federal_contract_opportunitiesSearch federal contract opportunities (SAM.gov)A

Search US federal contract opportunities (RFPs, solicitations, sources sought, award notices) from SAM.gov's official public data extract — including contracting-officer names, emails, and phone numbers. Filter by keyword, NAICS code, notice type, small-business set-aside, agency, place-of-performance state, and dates. Great for GovCon business development. Runs the paid Apify actor https://apify.com/cblu/sam-gov-contract-opportunities-scraper on YOUR Apify account (requires APIFY_TOKEN; pay per result: $0.004 per opportunity ($4.00 / 1,000), charged only for records actually returned).

ParametersJSON Schema

Name	Required	Description
`keyword`	No	Case-insensitive match against notice title, solicitation number, and description, e.g. 'janitorial', 'cybersecurity', 'drone'.
`popStates`	No	Two-letter place-of-performance state codes, e.g. ['TX', 'FL'].
`setAsides`	No	Small-business set-aside codes or label text, e.g. 'SBA' (total small business), '8A', 'WOSB', 'SDVOSBC', 'HZC' (HUBZone).
`activeOnly`	No	Only notices SAM.gov currently marks active (not archived). Set false for historical/award research.
`maxResults`	No	Max opportunities to return (1-5000, default 25). Each returned record is billed at $0.004 per opportunity ($4.00 / 1,000).
`naicsCodes`	No	NAICS industry codes; prefixes work, e.g. '541511' or just '54' for all professional services.
`noticeTypes`	No	Notice types (case-insensitive substring), e.g. 'Solicitation', 'Presolicitation', 'Sources Sought', 'Combined Synopsis', 'Award Notice'.
`postedAfter`	No	Only notices posted on/after this date (YYYY-MM-DD). Strongly recommended — makes runs much faster.
`postedBefore`	No	Only notices posted on/before this date (YYYY-MM-DD).
`agencyContains`	No	Case-insensitive substring match on department/sub-tier/office, e.g. 'VETERANS AFFAIRS', 'FOREST SERVICE', 'DEFENSE'.
`responseDueAfter`	No	Only notices whose response deadline is on/after this date — set to today for opportunities still open for bids.
`includeDescription`	No	Include the notice's full description text on every record.

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses pricing ($0.004 per opportunity), that it runs on an Apify actor, and requires APIFY_TOKEN. This is good transparency, though it could mention error handling or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that is front-loaded with the tool's purpose. It is concise and contains no wasted words, though it could be slightly more structured with bullet points for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should explain return values. It mentions some output fields (contracting-officer names, emails) but does not fully describe the structure of returned records. Given the tool's complexity (12 parameters), it is somewhat incomplete on outputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (all 12 parameters have descriptions). The tool description adds value beyond schema by explaining the pricing implication of maxResults and recommending postedAfter for performance. It does not introduce new parameters but enriches understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches US federal contract opportunities from SAM.gov, listing specific notice types (RFPs, solicitations, etc.) and data included. It distinguishes itself from sibling tools (building permits, healthcare providers) by targeting federal contracts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for GovCon business development and lists filters but does not explicitly state when to use it over alternatives or when not to use it. It provides context but lacks direct exclusions or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_healthcare_providersSearch US healthcare providers (NPI registry)A

Search the official CMS NPPES NPI Registry of all US healthcare providers and organizations. Returns NPI number, provider/organization name, specialty (taxonomy), state license, practice address with phone and fax, and for organizations the authorized official's name/title/phone. Filter by specialty, state, city, ZIP (wildcards like '331*'), or name. Great for healthcare sales lists, provider verification, and directory enrichment. Runs the paid Apify actor https://apify.com/cblu/npi-healthcare-providers-scraper on YOUR Apify account (requires APIFY_TOKEN; pay per result: $0.002 per provider record ($2.00 / 1,000), charged only for records actually returned).

ParametersJSON Schema

Name	Required	Description
`city`	No	Practice-location city, e.g. 'Austin'.
`state`	No	Two-letter US state code of the practice location, e.g. 'TX'.
`lastName`	No	Provider last name (individual lookups). Trailing wildcard supported.
`firstName`	No	Provider first name (individual lookups). Trailing wildcard supported, e.g. 'jo*'.
`maxResults`	No	Max provider records to return (1-5000, default 25). Each returned record is billed at $0.002 per provider record ($2.00 / 1,000).
`postalCode`	No	Practice-location ZIP. Prefix wildcards supported: '331*' matches all ZIPs starting 331 (greater Miami).
`enumerationType`	No	'individual' (NPI-1: physicians, dentists, nurses...) or 'organization' (NPI-2: clinics, hospitals, pharmacies...). Omit for both.
`organizationName`	No	Organization name (NPI-2 lookups). Trailing wildcard supported, e.g. 'mayo*'.
`taxonomyDescription`	No	Provider specialty / taxonomy, e.g. 'Dentist', 'Family Medicine', 'Chiropractor', 'Physical Therapist', 'Pharmacy'. Exact taxonomy codes also work.

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description carries full burden. It discloses the tool runs a paid Apify actor on the user's account, requires APIFY_TOKEN, and explains billing ($0.002 per record). This covers safety and cost implications well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat long but structured with key info upfront (what it is, what it returns, filters). Every sentence adds value: purpose, returned data, filters, use cases, and billing details. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 9 parameters, no output schema, and no annotations, the description provides sufficient context: it lists return fields, explains all filter parameters, and covers cost. It lacks only explicit mention of pagination or error handling, but overall it is quite complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptive parameter definitions. The description adds value by explaining wildcard usage (e.g., '331*', 'mayo*') and billing implications of maxResults. This enhances the agent's understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches the official CMS NPPES NPI Registry for US healthcare providers and organizations, listing returned fields and filter criteria. It distinguishes itself from sibling tools (building permits, federal contracts) by its specific domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases: 'healthcare sales lists, provider verification, and directory enrichment.' It does not specify when not to use this tool, but the clear purpose and unrelated siblings make this adequate.

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.

3 tool updatesv0.1.0Jul 12, 2026
- First observedsearch_building_permits
- First observedsearch_federal_contract_opportunities
- First observedsearch_healthcare_providers

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.3/5.0

Scored 2026-07-12 15:55 across 3 tools

Disambiguation5/5

Each tool targets a distinct and clearly separate domain: building permits, federal contract opportunities, and healthcare providers. There is no overlap in functionality or purpose.

Naming Consistency5/5

All three tools follow the same 'search_<domain>' naming pattern, making them predictable and easy to understand. The convention is consistent throughout.

Tool Count5/5

With only three tools, the set is small but well-scoped for the specific data sources it covers. Each tool serves a clear, valuable purpose without unnecessary bloat.

Completeness2/5

Despite the server name 'US Government Data' implying broad coverage, it only provides access to three narrow datasets (building permits from select cities, federal contracts, and healthcare providers). Many major government data categories are missing, such as census, federal spending, or regulations.

Maintenance

ActivityStale

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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us-govdata-mcp

Testen Sie es in 30 Sekunden — kein Konto, keine Kosten

Tools

Schnellstart

1. Apify-Token besorgen (kostenlos, ~2 Minuten)

2. Server zu Ihrem MCP-Client hinzufügen

3. Fragen Sie Ihren KI-Agenten Dinge wie

Transporte

Umgebungsvariablen

So funktioniert es

Entwicklung

Verwandte Themen

Lizenz

Available Tools

TDQS

TDQS

TDQS

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

DOL WHD MCP

PubRecords MCP

whetstone-mcpofficial

us-gov-data-mcp