# US Lobbying Disclosure Scraper - Senate LDA (`oriented_wallpaper/lobbying-disclosure-scraper`) Actor Scrape US federal lobbying disclosures from the official Senate LDA API — registrant (firm), client, income/expenses, issues lobbied, named lobbyists & targeted agencies. Filter by year/registrant/client/issue, dedupe. Export CSV/JSON/Excel. No API key. - **URL**: https://apify.com/oriented\_wallpaper/lobbying-disclosure-scraper.md - **Developed by:** [Flash Scrape](https://apify.com/oriented_wallpaper) (community) - **Categories:** News, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## US Lobbying Disclosure Scraper - Senate LDA **This lobbying scraper turns the official US Senate LDA database into a clean, queryable feed** — every federal lobbying disclosure filing, flattened into one row each: the **registrant** (lobbying firm), the **client** who paid, filing type/year/period, **income/expenses** spent on lobbying, the **issues** lobbied, the **named lobbyists**, and the **government entities** targeted — plus links to the filing and source document. Filter by year, registrant, client, or issue; export to CSV, JSON, or Excel. Built for **journalists, opposition & policy researchers, public-affairs / PR firms, and compliance teams** who need structured lobbying data — without paying enterprise prices (FiscalNote, Quorum). Official government data, **no API key, no anti-bot.** --- ### Why use this - **Authoritative source** — the official US Senate Lobbying Disclosure Act API (1.9M+ filings). - **Revolving-door detection** — flags every filing that names a lobbyist who previously held a **covered government position** (with the former role), and a `revolvingDoorOnly` filter. **No other LDA scraper does this** — it's the story journalists actually want. - **0-100 `influence_score`** — an explainable signal (spend + lobbyist headcount + issues + agencies targeted + revolving-door + foreign ties) so you can rank the heaviest efforts, with a `minInfluenceScore` filter. - **Surfaces the fields others drop** — `foreign_entities` (with country & ownership %), `affiliated_organizations`, `conviction_disclosures`, and `termination_date` — all flattened and labeled. - **Flattened + readable** — the LDA API nests lobbyists and issues several levels deep; this surfaces them as clean lists plus a single `amount_usd`. - **Follow the money** — see who paid whom, how much, on what issues, targeting which agencies. - **No key, no proxies** — public data; runs for free. #### Input | Field | Type | Description | |---|---|---| | `filingYear` | integer | Year of filings (e.g. `2024`). | | `registrantName` | string | Lobbying-firm name (partial match). | | `clientName` | string | Client (the paying org) name (partial match). | | `issueCode` | string | Issue area, e.g. `TAX`, `HCR`, `DEF`, `TEC`. | | `filingType` | string | `RR` (registration), `Q1`–`Q4` (quarterly reports). | | `revolvingDoorOnly` | boolean | Keep only filings with a former-government-official lobbyist. | | `minInfluenceScore` | integer | Keep only filings with `influence_score` ≥ this (0-100). | | `maxItems` | integer | Max filings. Default `200`. | | `apiKey` | string | Optional free LDA key for large runs. | **Example input:** ```json { "filingYear": 2024, "issueCode": "TEC", "maxItems": 500 } ```` #### JSON output sample ```json { "filing_uuid": "7866327b-c89...", "filing_year": 2024, "filing_period": "1st Quarter (Jan 1 - Mar 31)", "filing_type": "1st Quarter - Report", "influence_score": 71, "influence_breakdown": { "spend": 12, "lobbyists": 4, "issues": 4, "gov_targets": 6, "revolving_door": 25, "foreign_ties": 10 }, "revolving_door": true, "revolving_door_lobbyists": [ { "name": "Jane Doe", "former_position": "Legislative Director, Sen. Smith" } ], "registrant": "East Capitol Advisors", "registrant_state": "DC", "client": "CTIA - The Wireless Association", "client_state": "DC", "amount_usd": 30000.0, "income_usd": 30000.0, "expenses_usd": null, "issues": ["Telecommunications"], "lobbyists": ["Jane Doe", "John Roe"], "lobbyist_count": 2, "government_entities": ["U.S. Senate", "FCC"], "foreign_entities": [{ "name": "Example SARL", "country": "France", "ownership_percentage": 12.5 }], "has_foreign_ties": true, "affiliated_organizations": [{ "name": "Example Holdings USA", "state": "Texas", "country": "United States of America" }], "conviction_disclosures": [], "has_conviction_disclosure": false, "termination_date": null, "posted_date": "2024-01-02", "filing_url": "https://lda.senate.gov/api/v1/filings/7866327b...", "document_url": "https://...pdf" } ``` Results render as a clean, sortable table on the Output tab and export to CSV, JSON, or Excel. *** ### Use cases - **Journalism / oppo research** — who lobbied on a bill, for which client, spending how much. - **Public-affairs intelligence** — track competitors' and clients' lobbying activity over time. - **Compliance** — monitor registrant/client filings and lobbyist rosters. - **Market mapping** — aggregate spend by issue area, agency, or year. *** ### Use with AI agents & automation Run from the Apify **MCP** server so AI agents can query lobbying filings as a tool call, schedule runs via **Make**, **n8n**, or **Zapier** to alert on new filings for a client/issue, or sync to **Google Sheets**. Clean flat JSON drops into research pipelines with no glue code. *** ### Pricing **Pay-per-event — charged per filing delivered.** Source is the free public Senate LDA API (no proxy cost). See the Apify Store page for the current price. *** ### FAQ **Where's the data from?** The official **US Senate Lobbying Disclosure Act (LDA)** API at lda.senate.gov — public government data. **Do I need a key?** No. Add a free LDA key only for large/high-frequency runs (higher rate limit). **What's `amount_usd`?** The lobbying income (firm hired by a client) or expenses (in-house lobbying) reported on the filing; registrations often have none until the first quarterly report. **Can I export to CSV or Google Sheets?** Yes — CSV, JSON, or Excel from the Output tab, or sync via Make/n8n/Zapier. *** ### Other Flash Scrape scrapers - [FDA Recall Scraper](https://apify.com/oriented_wallpaper/fda-recall-scraper) — drug/device/food recalls - [NPI Healthcare Provider Scraper](https://apify.com/oriented_wallpaper/npi-healthcare-leads) — US provider leads - [Google SERP Scraper](https://apify.com/oriented_wallpaper/google-serp-scraper) — search rankings - [Trustpilot Reviews Scraper](https://apify.com/oriented_wallpaper/trustpilot-reviews-scraper) — company reviews # Actor input Schema ## `filingYear` (type: `integer`): Year of the lobbying filings to pull (e.g. 2024). ## `registrantName` (type: `string`): Filter by the registrant / lobbying firm name (optional, partial match). ## `clientName` (type: `string`): Filter by the client (the company/org paying for lobbying) name (optional, partial match). ## `issueCode` (type: `string`): Filter by lobbying issue, e.g. 'TAX', 'HCR' (health), 'DEF' (defense), 'TEC' (tech). Optional. ## `filingType` (type: `string`): Filter by filing type code (e.g. 'RR' registration, 'Q1'-'Q4' quarterly reports). Optional. ## `revolvingDoorOnly` (type: `boolean`): Return only filings that name at least one lobbyist who previously held a covered government position (a revolving-door signal). ## `minInfluenceScore` (type: `integer`): Only return filings with a computed influence score (0-100) at or above this. 0 = no filter. ## `maxItems` (type: `integer`): Maximum number of lobbying filings to return. ## `apiKey` (type: `string`): A free LDA API key (lda.senate.gov/api/register) raises the rate limit for large runs. Not required for normal use. ## Actor input object example ```json { "filingYear": 2024, "revolvingDoorOnly": false, "minInfluenceScore": 0, "maxItems": 200 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "filingYear": 2024 }; // Run the Actor and wait for it to finish const run = await client.actor("oriented_wallpaper/lobbying-disclosure-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "filingYear": 2024 } # Run the Actor and wait for it to finish run = client.actor("oriented_wallpaper/lobbying-disclosure-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "filingYear": 2024 }' | apify call oriented_wallpaper/lobbying-disclosure-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=oriented_wallpaper/lobbying-disclosure-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "US Lobbying Disclosure Scraper - Senate LDA", "description": "Scrape US federal lobbying disclosures from the official Senate LDA API — registrant (firm), client, income/expenses, issues lobbied, named lobbyists & targeted agencies. Filter by year/registrant/client/issue, dedupe. Export CSV/JSON/Excel. No API key.", "version": "0.1", "x-build-id": "r6SDMAPmxvnCgBhrC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/oriented_wallpaper~lobbying-disclosure-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-oriented_wallpaper-lobbying-disclosure-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/oriented_wallpaper~lobbying-disclosure-scraper/runs": { "post": { "operationId": "runs-sync-oriented_wallpaper-lobbying-disclosure-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/oriented_wallpaper~lobbying-disclosure-scraper/run-sync": { "post": { "operationId": "run-sync-oriented_wallpaper-lobbying-disclosure-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "filingYear": { "title": "Filing year", "minimum": 1999, "maximum": 2027, "type": "integer", "description": "Year of the lobbying filings to pull (e.g. 2024)." }, "registrantName": { "title": "Registrant (lobbying firm)", "type": "string", "description": "Filter by the registrant / lobbying firm name (optional, partial match)." }, "clientName": { "title": "Client", "type": "string", "description": "Filter by the client (the company/org paying for lobbying) name (optional, partial match)." }, "issueCode": { "title": "Issue area", "type": "string", "description": "Filter by lobbying issue, e.g. 'TAX', 'HCR' (health), 'DEF' (defense), 'TEC' (tech). Optional." }, "filingType": { "title": "Filing type", "type": "string", "description": "Filter by filing type code (e.g. 'RR' registration, 'Q1'-'Q4' quarterly reports). Optional." }, "revolvingDoorOnly": { "title": "Revolving-door filings only", "type": "boolean", "description": "Return only filings that name at least one lobbyist who previously held a covered government position (a revolving-door signal).", "default": false }, "minInfluenceScore": { "title": "Minimum influence score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only return filings with a computed influence score (0-100) at or above this. 0 = no filter.", "default": 0 }, "maxItems": { "title": "Max filings", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of lobbying filings to return.", "default": 200 }, "apiKey": { "title": "Senate LDA API key (optional)", "type": "string", "description": "A free LDA API key (lda.senate.gov/api/register) raises the rate limit for large runs. Not required for normal use." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```