4,000+ servers built on vurb.ts
Vinkius
LangChainFramework
Massive MCP Server

Bring Dividends
to LangChain

Learn how to connect Massive to LangChain and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

MCP Inspector GDPR Free for Subscribers
List Dividends

Compatible with every major AI agent and IDE

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
Massive

What is the Massive MCP Server?

Connect to Massive to retrieve comprehensive historical dividend data for thousands of tickers. Empower your AI agent to perform deep financial analysis and equity research through natural conversation.

What you can do

  • Historical Dividends — Fetch full records of cash distributions for any supported stock ticker from the Massive API.
  • Granular Filtering — Filter results by ex-dividend date, frequency (annual, quarterly), or specific distribution types.
  • Distribution Types — Identify recurring, special, supplemental, or irregular dividends to understand company payout patterns.
  • Data Analysis — Sort and limit results (up to 5000 records) to build precise financial models or investment reports.

How it works

  1. Subscribe to this server
  2. Enter your Massive API Key
  3. Start querying financial data from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Financial Analysts — quickly retrieve payout histories to calculate yields and dividend growth rates.
  • Investors — check upcoming or historical ex-dividend dates to manage portfolio timing.
  • Developers — integrate reliable financial distribution data into trading bots or research tools without complex scraping.

Built-in capabilities (1)

list_dividends

Retrieve historical cash dividends for a ticker

Why LangChain?

LangChain's ecosystem of 500+ components combines seamlessly with Massive through native MCP adapters. Connect 1 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

  • The largest ecosystem of integrations, chains, and agents. combine Massive MCP tools with 500+ LangChain components

  • Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

  • LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

  • Memory and conversation persistence let agents maintain context across Massive queries for multi-turn workflows

See it in action

Massive in LangChain

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

Massive and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect Massive to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

4,000+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself4,000+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for Massive in LangChain

The Massive MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 1 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Massive
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

The Vinkius Advantage

How Vinkius secures Massive for LangChain

Every tool call from LangChain to the Massive MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

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.

02

What types of dividend distributions can I identify?

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

03

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.

04

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

05

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.

06

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

07

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Explore More MCP Servers

View all →