Mcp Server Receipt

MCP Server Receipt
A specialized MCP server for automated receipt organization and naming

The MCP Server Receipt addresses a common bottleneck in financial workflows: the manual sorting, renaming, and archiving of paper‑oriented receipts that have been digitised as PDFs. In many organisations, receipts arrive in bulk, often with inconsistent naming conventions that hinder searchability and audit compliance. This server equips a language model with the context needed to standardise receipt handling, freeing developers from repetitive file‑management chores and enabling seamless integration into larger AI‑driven accounting pipelines.

When the server starts, it presents a single prompt—gen-receipt-filename—to the connected LLM. The model is instructed to parse each PDF, extract the transaction date, amount, and vendor name, then construct a filename in the format . The prompt contains no arguments, making it simple to invoke from any MCP‑compatible client. Once the filename is generated, the LLM copies the original PDF to a user‑specified output directory. This two‑step workflow—extraction followed by relocation—ensures that receipts are both easily identifiable and stored in a consistent location, ready for downstream processes such as expense reconciliation or tax preparation.

Key capabilities of this MCP server include:

• Automated metadata extraction from PDFs, leveraging the LLM’s natural‑language understanding to pull dates, monetary values, and company names even from scanned documents.
• Standardised naming convention that embeds critical information directly into the file name, improving discoverability and audit readiness.
• Simple directory configuration via command‑line arguments or a JSON host definition, allowing the server to be deployed in diverse environments (local machines, CI pipelines, or cloud functions).
• LLM‑driven file relocation that eliminates manual copying and reduces the risk of human error.

Typical use cases span small‑to‑mid sized businesses, freelancers, and accounting firms that receive frequent receipt uploads. For instance, an expense‑tracking application can trigger this MCP server whenever a new PDF lands in a shared folder; the LLM will rename and move it to a structured archive, after which an automated bookkeeping bot can ingest the data into accounting software. In audit scenarios, the consistent naming scheme simplifies evidence collection and verification.

Because the server relies solely on the LLM for parsing, it adapts to variations in receipt layouts and languages without needing custom OCR pipelines. This flexibility is a standout advantage: developers can deploy the same MCP server across multiple jurisdictions or industries, trusting that the model will handle diverse formats. Moreover, by exposing a single prompt and minimal configuration, the server integrates cleanly into existing MCP workflows, allowing developers to chain receipt processing with other AI tasks—such as expense categorisation or tax code assignment—without additional tooling overhead.