Moneybird MCP Server

The Moneybird MCP Server bridges the gap between conversational AI assistants and the Moneybird accounting ecosystem. By exposing a rich set of tools over the Model Context Protocol, it lets an assistant retrieve and manipulate accounting data—contacts, invoices, financial accounts, products, projects, and time entries—without the user writing any code. The server’s design focuses on flexibility: developers can extend or customize API calls, and the assistant can compose complex queries using Moneybird’s native filtering syntax.

The core value proposition is twofold. First, it removes the friction of integrating a third‑party accounting platform into AI workflows; developers no longer need to build bespoke connectors or maintain separate API wrappers. Second, it empowers non‑technical users to ask natural language questions that trigger precise data operations: “Show me all invoices from last month,” or “Add a new contact named Maria.” The assistant can then call the appropriate MCP tool, receive structured JSON, and present it in a conversational format.

Key capabilities include:

• Advanced Contact Management – list, filter by creation or update timestamps, create and update contact records. Filtering uses Moneybird’s query syntax (e.g., ), allowing fine‑grained retrieval.
• Financial Insight – access sales invoices, financial accounts, and payment records in a single query. The server can stream large datasets with response chunking to keep latency low.
• Business Operations – manage products, projects, and time entries directly from the chat interface, enabling real‑time updates to project budgets or product catalogs.
• Custom API Calls – expose any Moneybird endpoint that isn’t pre‑built into the server, giving developers full control over data access.
• Preconfigured Prompt – a ready‑made Moneybird assistant prompt streamlines onboarding for Claude Desktop users.

Typical use cases span small businesses and freelancers who rely on Moneybird for bookkeeping. An AI assistant can automatically generate monthly expense reports, reconcile payments, or suggest new product pricing based on historical data. In a larger enterprise setting, the server can be integrated into a broader AI‑powered ERP layer, allowing finance teams to query and update records across multiple departments through a single conversational interface.

Integration into an AI workflow is straightforward: once the server runs, the assistant declares a new MCP resource named “moneybird.” The assistant’s prompt can then reference tools like or . Because the server adheres to MCP’s standard schema, any AI platform that supports the protocol—Claude, Gemini, or others—can consume it with minimal configuration. The result is a seamless, code‑free bridge between natural language and robust accounting data.