Live Excel intelligence MCP server - queries OneDrive workbooks via Microsoft Graph with semantic routing. Structure is cached, cell data is always fetched live.
View on GitHub ↗A live Excel intelligence layer for AI agents. Point it at a OneDrive folder and your agent can ask questions about those spreadsheets in plain English, against the numbers that are in them right now.
Most spreadsheet integrations work by copying your data somewhere else. They ingest the workbook, chunk it, embed the cell values, and store the whole thing in a vector database. From that moment on your agent is answering questions about a snapshot. Someone updates the inventory sheet at 9am and the agent is still quoting Tuesday's numbers.
Structure gets cached. Filenames, sheet names, column headers, where the header row starts. This changes rarely, it is cheap to store, and it is what the agent needs in order to know what to ask for.
Data never gets cached. Not once. Every tool call that returns a number goes out to the Microsoft Graph API and pulls the current used range. There is no data cache to go stale, no sync job to fall behind, and no cell value written to disk anywhere in this project.
Every response carries a metadata.fetchedat timestamp and an iscached: false flag so the model can see, in band, that it is looking at fresh data.
A natural language question gets embedded, matched against the sheet descriptions by cosine similarity, and routed to the sheets most likely to hold the answer. Those sheets, and only those, get fetched live. Filtering and aggregation then happen in pandas on the freshly fetched frame.
From the project README.
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