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Google Finance MCP Tools for AI Agents

Let an agent retrieve stock summaries and historical price data for a ticker over a specified time window.

Available Tools

3 tools available in this integration

GoogleFinance.GetStockHistoricalData

Fetch historical stock price data over a specified time window

GoogleFinance.GetStockHistory

Fetch historical stock price data over a specified time window

GoogleFinance.GetStockSummary

Retrieve the summary information for a given stock ticker using the Google Finance API.

Why agent-optimized tools matter

Built for intent, not API schemas

Ask the agent to "compare these three stocks over the same six-month window." Arcade picks the right Google Finance tools without guessing whether to request summaries or historical prices first.

Up to 100x fewer tokens

Google Finance reads return a focused stock summary or historical price series, so the agent gets the requested market data without loading unrelated records into its context.

Complete the workflow end to end

Identify the tickers, retrieve their summaries, fetch historical prices, compare the selected window, and return the findings through one toolkit designed around the complete stock-research task.

Make actions predictable and controlled

Arcade tools return structured results and useful errors across users and runs. Teams can apply scope restrictions, redaction, and approval policies so agents follow the same controls every time.

Securing Google Finance

The more capabilities agents get, the more useful they are. However, more capabilities bring more risks of undesired effects such as data loss and exfiltration.

This is why Arcade provides you with contextual rules that dictate how and when a tool is allowed to run. Arcade’s contextual access lets you govern tool visibility and behavior at every stage of execution and control who can see a tool, what inputs are allowed, and what comes back.

Learn about Contextual Access Policies

For Google Finance, you can implement some of these policies:

Access when tools are listed for a user
  • Decide which tools an agent is allowed to see at all. A tool that is never listed cannot be called, whoever is asking.
Pre-execution before each tool call
  • Inspect the inputs a call is about to run with, and block it or send it for human approval when they fall outside what the agent should do unsupervised.
Post-execution after the tool returns
  • Deny the output of GoogleFinance.GetStockHistoricalData for tickers on your restricted-securities list, so an agent cannot use historical prices in prohibited trading analysis.
  • Redact the returned summary from GoogleFinance.GetStockSummary for securities under your confidential-deal policy, so restricted market information never reaches the model.

How to use Google Finance with your agent

Pick your MCP client below and follow the setup from authentication to your first stock lookup. Then give your agent prompts for stock summaries or historical price windows.

Your questions, answered

A Google Finance MCP server exposes Google Finance capabilities as structured tools that an AI agent can call through the Model Context Protocol. Through Arcade, an agent can retrieve stock summaries and historical price data using a shared API credential.

Arcade provides the MCP access layer for Google Finance rather than relying on a Google-hosted MCP endpoint. Arcade adds credential brokering, approval policies, response redaction, and access controls for agents and clients.

Arcade agents can retrieve a stock summary and fetch historical stock prices over a specified time window. These actions are read-only; they do not place trades, submit orders, or change market data.

Google Finance access requires a shared API key or secret with permission to use the Google Finance API. Configure that credential once; this integration does not use per-user Google OAuth scopes.

No. Users do not connect individual Google Finance accounts. A shared API key or secret is configured once, brokered by Arcade, and used for authorized calls without exposing the credential to the model.

Yes. Contextual Access policies can require human approval before a call proceeds, although this integration exposes read-only stock-data actions and no trading or other consequential write actions.

Arcade proxies Google Finance API calls and does not persist your content as part of normal tool execution. The shared credential is brokered and stored encrypted at rest, and the model never receives it.

Any framework or client that can connect to Arcade's MCP gateway or tool APIs works, including LangChain, OpenAI Agents, CrewAI, Claude Desktop, Claude Code, Cursor, Visual Studio Code, Microsoft Copilot Studio, and GitHub Copilot.

Arcade continues access while the configured credential remains valid. If the key or secret is revoked, rotated, or can no longer be used, calls stop until the credential is reconnected or replaced.

Calls are subject to the Google Finance API's rate limits and quotas, along with any limits attached to the shared credential. Repeated historical-data requests should be paced within those limits.

Ready to actually ship your agent?

Connect your agent to Google Finance with a shared API key, agent-optimized tools and approval controls for consequential actions.

Build Your Agent Read the Google Finance Quickstart