Chrome History MCP Server

Overview

The Chrome History MCP server bridges the gap between an AI assistant and a user’s local browsing history. By exposing the raw SQLite database that Chrome maintains, it allows AI tools to query, analyze, and summarize past web activity without requiring direct access to the browser or manual export steps. This capability is invaluable for developers building context-aware applications, forensic analysts, or productivity tools that need to understand a user’s online behavior over time.

Problem Solved

Modern AI assistants often lack persistent memory of a user’s interactions, especially when those interactions involve web browsing. Without a reliable source of historical data, the assistant can’t offer personalized recommendations or recall prior searches. Manually exporting history files is cumbersome and error‑prone, especially across operating systems. The Chrome History MCP server automates this process by providing a standardized API that reads the history database in real time, eliminating manual steps and ensuring up‑to‑date data is always available.

Core Functionality

• Database Access: Reads Chrome’s SQLite history file from the default location on Windows, macOS, or Linux, with an option to specify a custom profile path.
• Query Interface: Exposes endpoints that allow clients to retrieve URLs, visit counts, timestamps, and search queries in a structured format.
• Streaming Updates: Because the server monitors the history file, AI assistants can receive incremental updates as new pages are visited.
• Security‑First Design: The server runs locally and never transmits raw browsing data over the network, preserving user privacy.

Key Features

• Cross‑Platform Compatibility: Works seamlessly on all major operating systems with minimal configuration.
• Easy Integration: Can be launched as a child process from any MCP client, such as , and referenced in the server configuration JSON.
• Custom Path Support: Handles multiple Chrome profiles, enabling developers to target specific user accounts or test environments.
• Real‑Time Data: Provides near real‑time access to browsing history, making it suitable for live assistants that need up‑to‑date context.

Use Cases

• Personal Assistants: Offer follow‑up questions or reminders based on recent sites visited.
• Productivity Analytics: Generate reports of time spent on domains, identify productivity bottlenecks, or suggest site blocks.
• Digital Forensics: Quickly surface browsing patterns during investigations without manual data extraction.
• Research Tools: Correlate user behavior with experimental conditions in studies that involve web usage.

Integration Workflow

1. Start the MCP server with the appropriate path to the Chrome history file.
2. Configure the MCP client (e.g., ) to point to this server via its command and arguments.
3. Invoke the history endpoints from your AI assistant code, passing filters such as date ranges or search terms.
4. Process the returned data to enrich responses, generate summaries, or trigger actions.

The server’s lightweight design and straightforward configuration make it a plug‑and‑play component in any AI‑driven workflow that benefits from historical web context.