Sign in Book a demo
Back to Tools
Search API Key BYOCPro
Build Your Agent View Google Finance Docs
google-finance logo

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

2 tools available in this integration

GoogleFinance.GetStockHistoricalData

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 "research the stock ticker I'm considering and show its recent trend." Arcade helps it use the right Google Finance tools without guessing ticker formats, date ranges or raw API parameters.

Up to 100x fewer tokens

Google Finance reads return a stock summary or time-bounded historical prices instead of a broad market response. The agent gets the figures needed for research without loading unrelated price data into the model.

Complete the workflow end to end

Identify a ticker, read its summary, pull a defined historical window, compare the prices, 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 financial-data capabilities as structured tools an AI agent can call through the Model Context Protocol. For this integration, the agent can retrieve a stock summary or historical prices for a specified time window.

Google Finance does not provide the first-party MCP endpoint used here. Arcade hosts the integration and adds a shared-key runtime, agent-optimized actions, approval policies, redaction, and a consistent MCP and tool API for supported clients.

Arcade agents can retrieve summary information for a stock ticker and fetch its historical price data over a specified time window. The integration does not provide trading, portfolio-management, or other write actions.

This integration uses a shared API key or secret configured once. It does not use per-user Google OAuth permissions; access is limited by what the configured credential can reach.

No. Users do not connect individual Google Finance accounts for this integration. One shared credential is configured for the integration, brokered by Arcade, and never passed to the model.

There are no write or trading actions in this integration, so there is no consequential Google Finance action to approve. Contextual Access policies can still require human approval before either data request proceeds, and can redact returned fields or hide the actions from an agent.

Arcade proxies Google Finance API calls and does not persist your financial data 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.

Because access uses a shared API key or secret, calls continue while that credential is valid. If it expires, is rotated, revoked, or can no longer be used, calls stop until the credential is reconfigured or replaced.

Requests remain subject to the Google Finance API's rate limits and the quotas associated with the configured key or secret. No toolkit-specific quota or per-call limit is specified here, so plan for the limits imposed by the underlying API and credential.

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