QuickBooks Time MCP Server (Combined)

QuickBooks Time MCP Server (Combined)
An all‑in‑one gateway to the QuickBooks Time API, bundled into a single, easy‑to‑deploy MCP server.

The QuickBooks Time ecosystem exposes a wealth of data—job codes, timesheets, users, projects, and more—through separate API endpoints. For developers building AI assistants that need to query or manipulate this data, managing multiple MCP servers can become cumbersome. This combined server consolidates the four legacy QuickBooks Time MCP services (JobCode, Reports & Core, Timesheet, and User tools) into one cohesive interface. By doing so, it eliminates the need to maintain separate server processes and simplifies configuration for AI assistants like Claude or other MCP‑compatible agents.

At its core, the server offers a rich set of tools that mirror QuickBooks Time’s REST capabilities. Developers can retrieve job codes with fine‑grained filters, navigate full jobcode hierarchies, and access timesheet records either by ID or through pagination. User management is equally robust: bulk user listings, individual lookups, and group retrievals are all exposed. Additionally, project data can be queried with optional filters for modification dates and pagination controls. Each tool is designed to return the same JSON structure as QuickBooks Time, ensuring seamless integration into existing data pipelines or AI workflows.

The value proposition for AI assistants lies in the server’s single‑point access model. A conversational agent can issue a single “get_jobcodes” or “get_timesheet” command, and the MCP server will translate that into the appropriate QuickBooks Time API call, handle authentication via a bearer token, and return structured data. This removes the need for custom HTTP clients or OAuth flows within the assistant’s codebase, allowing developers to focus on higher‑level logic such as scheduling reports or automating time entry approvals.

Real‑world use cases include:

• Automated reporting: An AI assistant can pull the latest timesheet data, aggregate hours by project or employee, and generate a PDF report on demand.
• Dynamic scheduling: By querying job codes and current timesheets, a bot can suggest optimal task assignments or flag overtime violations.
• User onboarding: New hires’ profiles and group memberships can be fetched automatically, enabling AI‑driven welcome workflows.
• Project cost tracking: Project data combined with timesheet entries allows assistants to compute billable versus non‑billable hours in real time.

Integration with AI workflows is straightforward. Once the MCP server is running, developers add it to their assistant’s configuration (e.g., via Claude Desktop’s section). The assistant then references the server by name () and invokes tools using natural language prompts. Because all tool definitions are exposed through the MCP schema, type‑checked calls and auto‑completion become available in IDEs or conversational UI editors.

Unique advantages of this combined server include:

• Unified authentication: A single access token powers all endpoints, reducing credential management overhead.
• Consistent API surface: Despite the underlying complexity of QuickBooks Time’s separate services, developers interact with a single, predictable set of tools.
• Community‑driven evolution: The project welcomes contributions and improvements, encouraging a collaborative ecosystem around QuickBooks Time automation.

In summary, the QuickBooks Time MCP Server (Combined) streamlines access to a comprehensive suite of time‑tracking data, enabling AI assistants to deliver powerful, context‑aware automation without the friction of managing multiple services or custom HTTP clients.