Finance and payments · MCP server
Whale data MCP: MCP server, setup and security
Whale data MCP is an open-source MCP server that lets an AI agent inspect Polymarket settlement risks and delayed large trader transaction data. Its repository has 1 stars and its last commit is from October 22, 2026 and it is licensed under MIT.
What Whale data MCP does
According to its repository: “Polymarket data for agents from Predge: free ed25519-signed UMA settlement-risk records for any market, read live from Polygon, and an offline record verifier; plus paid whale trades (≥$10k, 15-min delay), wallet leaderboards and smart-money consensus at $0.005–$0.03 per call, paid in USDC over x402”
An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Whale data MCP is listed under Finance and payments, a category of 202 servers in the directory, where it ranks #178 by stars.
Topics declared by the repository: ai-agents, base, polymarket, prediction-markets, usdc, whale-tracking.
Installing and connecting Whale data MCP
Distribution modes declared in the official MCP registry:
- npm package (Node.js, usually started with
npx)
Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: TypeScript.
The registry lists 2 secret variables to provide (API key, access token). Keep them in the client's environment variables, never in a shared file or a repository.
Security: what to check
An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.
Points found for Whale data MCP:
- Secrets: the server acts with your credentials. Create a dedicated key with minimum rights and an expiry date.
Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.
Project activity and maintenance
Created on July 20, 2026, the predgeAI/whale-data-mcp repository has 1 stars and 0 forks, with 1 open issues. It has more stars than 7% of the servers in the directory. It received changes this month. Version published in the registry: 0.2.2 (October 18, 2026).
Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.
Verdict
Whale data MCP is a reasonable choice; check the points below before connecting it.
Strengths
- Maintained by the service's own vendor
- Active project: recent commit
- Listed in the official MCP registry
- Permissive licence (MIT)
Limitations
- Requires an API key or token
- Few visible users
Avoid if…
- You do not want to give credentials to an agent
Alternatives
- TradingMCP5.1K ★
- Finance Toolkit5.5K ★
- Tradememory protocol1.4K ★
- Tapetide Indian Stock Market MCP141 ★
- DexPaprika113 ★
- CNEquity846 ★
Learn more
Frequently asked questions
How do I install Whale data MCP?
Whale data MCP is distributed as npm package (Node.js, usually started with npx). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of predgeAI/whale-data-mcp.
Is Whale data MCP free?
The code is published under the MIT licence and can be used free of charge. It needs an API key: the service it connects to may be paid.
Is Whale data MCP safe?
Points to watch: secrets. Give it minimum rights and approve sensitive actions.
Is it an official server?
Yes: the awesome-mcp-servers list marks it as the service vendor's official implementation.
What are the alternatives to Whale data MCP?
In the same category: TradingMCP, Finance Toolkit, Tradememory protocol, and Tapetide Indian Stock Market MCP. TradingMCP and Finance Toolkit score higher on our grid.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score