Excel2JSON MCP Server

Overview

The Excel2JSON MCP server is a purpose‑built service that bridges the gap between traditional spreadsheet data and modern JSON‑driven AI workflows. By exposing a simple, well‑documented MCP endpoint, it lets Claude and other model assistants ingest Excel workbooks directly, converting rows, columns, and even complex merged cells into clean, structured JSON objects. This eliminates the need for manual data wrangling or intermediary scripts, allowing developers to focus on higher‑level logic and analytics.

The server solves a common pain point: spreadsheets remain the de facto format for data collection, yet most AI models and downstream services expect JSON. Excel2JSON automatically maps each worksheet to a separate array, preserves the original row numbers for traceability, and handles merged cells by expanding them into repeated values. Its Unicode support ensures that Chinese characters or other language scripts are rendered accurately, a critical feature for global teams. Robust validation and error handling surface issues such as corrupted files or unsupported formats early, preventing silent failures in downstream pipelines.

Key capabilities include:

• Multi‑sheet extraction – every sheet becomes a distinct JSON array, accessible via the MCP tool interface.
• Merged‑cell resolution – merged ranges are expanded so that every logical cell has a value, maintaining data integrity.
• Row‑number retention – each JSON record carries its original Excel row index, aiding debugging and audit trails.
• Unicode fidelity – full support for Chinese and other non‑ASCII characters, ensuring accurate text representation.
• Graceful error handling – the server validates file structure and reports detailed errors back to the client.

Typical use cases span data migration, reporting automation, and AI‑powered analytics. For instance, a data scientist can upload an Excel report to the MCP server, retrieve JSON via Claude’s tool invocation, and feed it directly into a language model prompt that generates insights or visualizations. In a BI pipeline, the server can serve as an ingestion point for spreadsheet‑based datasets before they are stored in a database or fed into a machine learning model.

Integration is straightforward: developers add the server’s MCP endpoint to their Claude configuration, then reference the provided tools in prompts. The server returns JSON that can be consumed by downstream code or further processed with additional MCP tools (e.g., filtering, aggregation). Its lightweight design and focus on a single transformation task make it an ideal component in larger AI‑centric workflows, where quick, reliable conversion from Excel to JSON is essential.