Vinkius
Massive

Supercharge your AI with Massive. Find historical stock dividend payouts instantly.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Massive MCP on Cursor AI Code Editor MCP Client Massive MCP on Claude Desktop App MCP Integration Massive MCP on OpenAI Agents SDK MCP Compatible Massive MCP on Visual Studio Code MCP Extension Client Massive MCP on GitHub Copilot AI Agent MCP Integration Massive MCP on Google Gemini AI MCP Integration Massive MCP on Lovable AI Development MCP Client Massive MCP on Mistral AI Agents MCP Compatible Massive MCP on Amazon AWS Bedrock MCP Support

Connect to your AI in seconds.

The `list_dividends` tool fetches full historical cash dividend records for any supported stock ticker. Your AI agent runs this function by accepting parameters like the ticker, date range, and required frequency (annual, quarterly).

This gives you a clean dataset of past payouts needed for deep financial modeling and equity research.

What your AI can do

List dividends

Retrieves historical cash dividend payouts for any specified stock ticker.

Fetch historical payout data

Your agent retrieves the full record of cash dividends for a specific stock ticker.

Filter by payment type and date

The tool lets you filter results to isolate special, recurring, or supplemental distributions based on dates.

Analyze dividend frequency trends

You can query for consistency across different frequencies (e.g., quarterly vs. annual) to track payment patterns.

Calculate historical yields

By providing the necessary payout data, your agent calculates dividend growth rates and historical yields.

Compatible AI Apps

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ any other MCP app
Included with Plan

Waiting for input…

AI Agent

Massive MCP Server: 1 Tool for Dividend Analysis

The single `list_dividends` tool lets you pull clean, structured data on past stock payouts and distribution history.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Massive on Vinkius

List Dividends

Retrieves historical cash dividend payouts for any specified stock ticker.

Connect to your AI in seconds. Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Massive integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on every call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Massive, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,000+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Every connection is secured and compliant automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
Massive MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Massive. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 1 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Manual dividend research sucks time.

Before MCP servers, checking a company's payout history meant opening multiple financial websites. You’d find annual reports here, quarterly data there, and sometimes the special payments were tucked away in a press release you had to manually read. It was hours of copy-pasting dates and amounts into Excel just to build a basic timeline.

Now, your agent handles it. You tell it: 'Give me the dividend history for AAPL.' The system runs `list_dividends`, pulls everything—special, regular, annual—and gives you one clean, structured list of payouts. It’s immediate.

Massive MCP Server: Massive's `list_dividends` tool.

You no longer have to piece together a payout history from half-dozen sources, each with different date formats and data schemas. The pain points around manual aggregation—the mismatched column headers, the missing special dividend records—are gone.

It’s simple: you ask your agent for historical dividends. It gets it right every time.

What your AI can actually do with this

You're gonna run complex finance queries without ever needing to mess with an API key or a giant spreadsheet. This server hooks your AI client up to the raw historical payout data you need for deep equity research.

The list_dividends tool fetches full records of cash dividend payouts for any stock ticker you throw at it. Your agent runs this function, and it gives you a clean, exhaustive dataset of past company distributions needed for serious financial modeling. You're analyzing patterns here; you ain't just checking a number.

When you use list_dividends, your AI client retrieves the complete dividend history—every payment counts, whether it was a regular handout or some one-off special distribution. It grabs all cash payouts, so you get the full story on how much money companies are sending back to shareholders over time. You can track every recurring payout and even isolate those supplemental payments that throw off simple calculations.

The tool lets your agent filter results way down, letting you isolate specific payment types or restrict results based on exact dates. Need to see only the special dividends paid out in Q4? Or maybe you want to check payouts strictly from quarterly cycles versus annual ones? You just tell it what you're looking for, and it narrows the focus immediately.

Because the data is so granular, your AI client can track dividend consistency across different frequencies. It helps you see if a company sticks to its payment schedule—whether it's quarterly, or if they only pay once a year. This reveals crucial patterns in corporate commitment that simple charts miss.

It’ll pull together the necessary payout data so your agent calculates key metrics like dividend growth rates and historical yields. You don't need another spreadsheet program to calculate this; the raw data feeds the model, and you get the resulting financial insights back directly. This makes building precise financial models fast.

The server pulls full records of cash payouts for any supported ticker, giving you a massive dataset ready for your analysis. It handles the heavy lifting, gathering every single historical payment record—recurring, special, or supplemental—into one place. The tool allows filtering by ex-dividend date and lets you specify the desired payment frequency to keep your data tight.

When your agent processes this data, it compiles a massive history of payouts, giving you access to thousands of records per ticker. It’s built for serious deep dives into corporate finance, letting you model payout trends over decades without running into data caps or formatting headaches.

The capability to calculate historical yields and track dividend growth rates is what makes this server essential. You get the core payout figures needed to run those calculations yourself, meaning your research remains precise and auditable. It keeps the flow of information moving so you can focus on interpreting the numbers, not cleaning them up.

You'll use this to build sophisticated financial models that track how a company’s payouts have evolved through different economic cycles. You can cross-reference payment types—for instance, comparing consistent quarterly payments against larger, infrequent special distributions—to understand management's true commitment to shareholders. It gathers the full context of cash returns for every ticker it supports.

It processes massive amounts of financial data efficiently. When you set parameters like a specific date range and request payout frequency, the tool delivers only the relevant records. This means your AI client doesn't choke on irrelevant noise; it gets exactly what it needs—the raw, unfiltered historical dividend record for immediate use in your analysis.

Built · Hosted · Managed by Vinkius Massive-MCP Server - List Dividends Data Access
Server ID 019e38bd-cba8-73c5-afd3-cc04e1e6b172
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

Can I filter dividends by a specific date? +

Yes. You can use the ex_dividend_date parameter in the list_dividends tool to find distributions occurring on or after a specific YYYY-MM-DD date.

What types of dividend distributions can I identify? +

The list_dividends tool supports filtering by distribution_type, including 'recurring', 'special', 'supplemental', 'irregular', and 'unknown'.

How many dividend records can I retrieve at once? +

By default, the list_dividends tool returns 100 results, but you can increase the limit parameter up to a maximum of 5000 records per query.

How do I authenticate when using `list_dividends`? +

You must provide your Massive API key during server setup. Vinkius securely manages this credential, allowing your AI client to access the historical data without exposing raw keys.

What happens if I run `list_dividends` with an invalid stock ticker? +

The system returns a specific API error message. Your agent will relay this exact code, telling you precisely why the query failed and what input needs correction.

Does `list_dividends` require parameters other than the stock ticker? +

No, initially providing the ticker is enough to start. You can then refine results in subsequent prompts by specifying frequency or distribution type for deeper analysis.

What historical depth can I retrieve using `list_dividends`? +

The API provides comprehensive data spanning many years of a ticker's trading life. You can pull decades of payout history, limited only by the company’s record.

What format is the dividend data delivered in for analysis? +

Data arrives in a structured JSON format. This makes it simple to pipe directly into financial models or Python scripts without requiring complex parsing steps.

Built & Managed by Vinkius 30s setup 1 tools

We've already built the connector for Massive. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 1 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.

Zero hosting required Full MCP catalog included Enterprise-grade security Auto-updated by Vinkius

Built, hosted, and secured by Vinkius. You just connect and go.