HLedger MCP Server

The HLedger MCP Server bridges the gap between AI assistants and real‑world accounting data by exposing the full power of the HLedger command line through a standardized Model Context Protocol interface. Instead of writing custom parsers or building bespoke APIs, developers can simply query balances, generate financial statements, and even modify journal entries with the same toolset they already use in their local workflow. This eliminates duplication of effort and ensures that AI‑driven insights are always grounded in the authoritative ledger maintained by HLedger.

At its core, the server offers a rich set of accounting tools that mirror the most common commands. Developers can list accounts, produce balance reports, view transaction registers, and print raw journal entries—all via simple MCP calls. The financial reporting suite goes further, providing ready‑made balance sheets, equity reports, income statements, and cash flow analyses. These tools are valuable for rapid prototyping of audit dashboards, automated reporting pipelines, or conversational assistants that answer “What is our net profit?” in real time.

Beyond reporting, the server includes powerful data‑analysis primitives. Stats and activity commands reveal transaction frequency and account usage patterns, while payee, description, tag, and note queries let AI agents surface trends or flag anomalies. The ability to list all source files () as MCP resources means that clients can inspect or retrieve the underlying journal data directly, fostering transparency and traceability.

The update layer is equally robust. With transactional safeguards—dry‑run support, exact text matching, and optional validation—the server allows AI assistants to add, replace, or remove entries safely. Batch imports, closing book transactions, and rewrite operations enable automated bookkeeping workflows that would otherwise require manual intervention. The optional web interface integration lets agents launch or manage instances on demand, providing a visual ledger view without leaving the MCP session.

In practice, HLedger MCP shines in scenarios such as automated bookkeeping assistants that reconcile expenses on the fly, AI‑driven financial analysts that generate quarterly reports from raw journal data, or chatbot interfaces that answer accounting questions while preserving audit trails. By delivering a single, protocol‑compliant endpoint to all of HLedger’s functionality, the server empowers developers to embed sophisticated financial intelligence into AI workflows with minimal friction.