# 📋 Regulatory Filings MCP (`nexgendata/regulatory-filings-mcp`) Actor MCP server bundling 17 SEC + institutional analytics actors as agent tools — WhaleWisdom / 8-K Push alternative - **URL**: https://apify.com/nexgendata/regulatory-filings-mcp.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** Business, AI, Automation - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $27,200.00 / 1,000 regulatory filings tool calls This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## 📋 Regulatory Filings MCP > **The MCP server hedge fund analysts, activist-strategy desks, and VC researchers wire into their agents to replace WhaleWisdom, 8-K Push, PitchBook, and Bloomberg Terminal lookups — 17 tools covering every SEC filing that moves a stock, plus institutional + sovereign-wealth-fund tracking, options unusual activity, short interest, and the IPO / earnings calendar. Per-call PPE pricing, no $24K/yr seat.** Pipe SEC EDGAR Form 4 / D / 8-K / 13F, Schedule 13D activist filings, derived insider clusters, 13F position deltas, SWF holdings, IPO + earnings calendars, analyst targets, pre-IPO secondary prices, options unusual activity, short interest, and dividend aristocrats straight into Claude, Cursor, Cline, Windsurf, ChatGPT, or any agent that speaks MCP. Built by nexgendata on Apify Standby — sub-second cold start, structured JSON, zero plumbing. --- ### 👤 Who buys this - **Hedge fund analysts** running insider-cluster + 13F-delta + Schedule 13D pipelines on a Claude agent — replaces a $90/mo WhaleWisdom Premium seat per analyst. - **Activist-strategy desks** tracking who's filing 13D/13G against which target — replaces an $8K/yr 13D Monitor subscription. - **VC + growth-equity researchers** monitoring SEC Form D private offerings + pre-IPO secondary prices for SpaceX / Stripe / OpenAI tier names — replaces PitchBook at $1000+/mo. - **Event-driven traders** wiring Form 8-K material events + corporate actions + earnings revisions into a real-time agent — replaces 8-K Push at $200/mo. - **Quant researchers** backtesting insider clusters + options unusual activity signals — replaces a Bloomberg Terminal seat at $24K/yr. --- ### 🛠️ The 17 tools #### SEC core filings | Tool | What it returns | |------|------| | `get_form_4_insider_trades(ticker, days_back, min_value_usd)` | SEC Form 4 — officers/directors buying or selling their own stock | | `get_form_d_private_funding(state, days_back, min_amount)` | SEC Form D — private offerings, hedge fund launches, exempt securities | | `get_form_8k_material_events(ticker, event_type, days_back)` | SEC Form 8-K — M&A, executive changes, bankruptcy, earnings, going concerns | | `get_form_13f_holdings(filer_cik, quarter)` | SEC Form 13F-HR — institutional position disclosures ($100M+ AUM) | | `get_schedule_13d_activist(target_ticker, filer, days_back)` | SEC Schedule 13D / 13G — activist filings (>5% stake) | #### Derivative analytics (premium tier) | Tool | What it returns | |------|------| | `detect_insider_cluster(ticker, days_window, min_insiders)` | Multi-insider buying clusters — the smart-money signal | | `get_13f_delta(filer_cik, days_back)` | New / increased / reduced / exit positions vs prior 13F filing | | `get_swf_holdings(fund, quarter)` | Sovereign wealth fund US equity positions — Norway GPFG, GIC, ADIA, PIF | #### Calendar / events | Tool | What it returns | |------|------| | `get_ipo_calendar(days_forward)` | Upcoming IPOs — pricing date, shares, range, underwriters | | `get_earnings_calendar(days_forward, ticker)` | Upcoming earnings — report dates, EPS + revenue estimates | | `get_earnings_estimates(ticker, days_back)` | Analyst EPS estimate revisions | | `get_analyst_targets(ticker)` | Wall Street price targets — high, low, mean, latest changes | | `get_pre_ipo_secondary(company)` | Pre-IPO secondary prices — Forge, EquityZen, Hiive | #### Activity / unusual | Tool | What it returns | |------|------| | `get_options_unusual_activity(ticker, min_volume_ratio)` | Volume vs OI spikes, large blocks, suspected smart-money positioning | | `get_short_interest(ticker, days_back)` | Short ratio, days-to-cover, % float short, changes vs prior | | `get_stock_splits_corporate_actions(days_forward)` | Splits, spinoffs, mergers, special dividends | | `get_dividend_aristocrats(min_years)` | S&P 500 companies with 25+ years of dividend increases | --- ### ⚡ Install #### Claude Desktop Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "regulatory-filings": { "transport": "streamable-http", "url": "https://nexgendata--regulatory-filings-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ```` #### Cursor Add to your `~/.cursor/mcp.json`: ```json { "mcpServers": { "regulatory-filings": { "url": "https://nexgendata--regulatory-filings-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ``` #### Cline / Windsurf Same pattern — point your MCP client at: ``` https://nexgendata--regulatory-filings-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN ``` Get an Apify token at https://console.apify.com/account/integrations. *** ### 🤖 Example agent workflows #### "Find clusters of insider buys in semis last 14 days" ``` Agent → detect_insider_cluster(days_window=14, min_insiders=3) → filter results to sector="Semiconductors" → for each cluster: get_form_4_insider_trades(ticker=X, days_back=14) → return: NVDA (4 insiders, $12M), AMD (3 insiders, $3.8M), AVGO (3 insiders, $2.1M) ``` #### "Diff this 13F filer's Q3 vs Q4 holdings" ``` Agent → get_13f_delta(filer_cik="0001067983", days_back=120) ## Berkshire → group by action: new_positions, increases, decreases, exits → for top 5 by $-delta: get_form_4_insider_trades(ticker=X) → return: Berkshire added DPZ ($1.1B), exited PARA, trimmed AAPL by 100M sh ``` #### "Alert when SWF reduces NVDA position" ``` Agent → cron: get_swf_holdings(quarter="latest") → compare against last snapshot in agent memory → if NVDA position change < -10%: notify → enrich: get_schedule_13d_activist(target_ticker="NVDA") + get_form_4_insider_trades(ticker="NVDA", days_back=30) ``` #### "Pre-earnings setup for upcoming reports" ``` Agent → get_earnings_calendar(days_forward=7) → for each ticker: get_earnings_estimates(ticker, days_back=21) ## estimate trend get_analyst_targets(ticker) ## consensus target get_options_unusual_activity(ticker) ## smart money positioning get_short_interest(ticker) ## squeeze risk → return: ranked report with conviction score ``` #### "Activist target screen" ``` Agent → get_schedule_13d_activist(days_back=30) → for each new 13D filing: get_form_8k_material_events(ticker, days_back=7) get_short_interest(ticker) → return: new 13D targets ranked by short squeeze potential ``` #### "VC funding map" ``` Agent → get_form_d_private_funding(state="CA", days_back=14, min_amount=10_000_000) → enrich with pre-IPO secondary prices: get_pre_ipo_secondary(company=X) → group by sector + funding round size → return: California raises >$10M last 2 weeks ``` *** ### 💰 Pricing — transparent, per-call | Event | Price | |------|------| | MCP session start | **$0.02** (one-time per session) | | Filings tool call | **$0.08** per call | | Derived analytics returned (cluster / delta / SWF) | **+$0.20** premium | A typical analyst workflow — ~50 tool calls/day, 10 of which hit analytics tier — runs ~**$6/day** ≈ $130/mo. A heavy quant pulling 500 calls/day runs ~$60/day. #### Compared to the incumbents | Service | Cost | Coverage | |------|------|------| | **Regulatory Filings MCP** (this) | **~$130/mo typical analyst** | All 17 SEC + institutional + activity tools | | WhaleWisdom Premium | $90/mo per seat | 13F only — no 8-K, no insider clusters, no SWF | | 8-K Push | $200/mo | 8-K alerting only — no 13F, no insider, no options | | PitchBook | $1000+/mo per seat | Private market + VC — no SEC filings | | Bloomberg Terminal | $24,000/yr per seat | Everything — but you're a Bloomberg user | | Refinitiv Eikon | $22,000/yr per seat | Everything — same as Bloomberg | If a hedge fund replaces 1 WhaleWisdom seat + 1 8-K Push seat ($290/mo combined) with this MCP wired into Claude, they're paying ~$130/mo for broader coverage and agent-native delivery. *** ### 🔗 Sister actors / cross-links If you're building an institutional research stack on nexgendata, you'll also want: - [Global Equities Screener MCP](https://apify.com/nexgendata/global-equities-screener-mcp?fpr=2ayu9b) — international exchange screeners (TSX, LSE, ASX, JPX, HKEX, NSE, B3, etc.) - [Sales Intelligence MCP](https://apify.com/nexgendata/sales-intelligence-mcp?fpr=2ayu9b) — Crunchbase / LinkedIn / contact enrichment for the management teams behind the filings - [Finance MCP Server](https://apify.com/nexgendata/finance-mcp-server?fpr=2ayu9b) — Yahoo Finance, Finviz, CoinGecko, FX rates - [SEC Form 4 Insider Trading Scraper](https://apify.com/nexgendata/sec-form-4-insider-trading-scraper?fpr=2ayu9b) — standalone Form 4 actor (the engine behind this MCP's Form 4 tool) - [13F Holdings Delta Tracker](https://apify.com/nexgendata/13f-holdings-delta-tracker?fpr=2ayu9b) — standalone delta engine - [Insider Cluster Detector](https://apify.com/nexgendata/insider-cluster-detector?fpr=2ayu9b) — standalone cluster signal - [Sovereign Wealth Fund Tracker](https://apify.com/nexgendata/sovereign-wealth-fund-tracker?fpr=2ayu9b) — standalone SWF holdings - [Schedule 13D Activist Tracker](https://apify.com/nexgendata/sec-schedule-13dg-activist-tracker?fpr=2ayu9b) — standalone activist filings *** ### 🧰 Tech - FastMCP + Apify Standby (streamable-http transport) - Python 3.12 on `apify/actor-python:3.12` - 17 tools, each wrapping a verified nexgendata SEC / institutional / event actor - Session middleware idles out after 300s (recoups on next session start) - Pay-per-event — no subscription, no seat lock-in *** ### 📬 Support Open an issue on the actor page or DM nexgendata on Apify. We ship fixes inside a day for paying users. Affiliate link: [apify.com/nexgendata/regulatory-filings-mcp?fpr=2ayu9b](https://apify.com/nexgendata/regulatory-filings-mcp?fpr=2ayu9b) # Actor input Schema ## `enableServer` (type: `boolean`): Enable MCP server mode (required for MCP usage) ## `port` (type: `integer`): Port to run the MCP server on ## Actor input object example ```json { "enableServer": true, "port": 3000 } ``` # 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 = { "enableServer": true, "port": 3000 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/regulatory-filings-mcp").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 = { "enableServer": True, "port": 3000, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/regulatory-filings-mcp").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 '{ "enableServer": true, "port": 3000 }' | apify call nexgendata/regulatory-filings-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/regulatory-filings-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "📋 Regulatory Filings MCP", "description": "MCP server bundling 17 SEC + institutional analytics actors as agent tools — WhaleWisdom / 8-K Push alternative", "version": "0.0", "x-build-id": "Zq5dEGndXMzaobDSl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~regulatory-filings-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-regulatory-filings-mcp", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~regulatory-filings-mcp/runs": { "post": { "operationId": "runs-sync-nexgendata-regulatory-filings-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~regulatory-filings-mcp/run-sync": { "post": { "operationId": "run-sync-nexgendata-regulatory-filings-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "enableServer" ], "properties": { "enableServer": { "title": "Enable MCP Server", "type": "boolean", "description": "Enable MCP server mode (required for MCP usage)", "default": true }, "port": { "title": "Server Port", "type": "integer", "description": "Port to run the MCP server on", "default": 3000 } } }, "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 } } } } } } } } } } ```