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Turn Excel/CSV folders into a traceable, evidence-backed knowledge layer.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "TableRAG" yet — see the docs or source repo.
Scan this Excel/CSV folder and list each file’s columns, column types, and possible primary keys.
A file-level schema overview that helps me quickly understand the data layout.
Using the tables in this folder, query monthly sales for 2024 and provide file sources and row evidence.
Deterministic query results with traceable evidence citations.
Search this CSV/Excel folder for “refund reason”, find relevant records, and show which files they appear in.
Relevant matches with file locations and contextual evidence.
Data analysts or operations teams with many Excel/CSV files can use it to unify viewing and retrieval. It turns a folder into a read-only, traceable data knowledge layer for later queries.
Researchers or product managers inheriting a new dataset often need to know the tables, fields, and relationships first. Its schema discovery helps them understand the structure fast.
When you need to answer where a conclusion came from, it can return traceable evidence. It fits audit, review, and source-citation workflows.
TableRAG is an MCP tool that turns Excel/CSV folders into a traceable, read-only AI knowledge layer. It supports deterministic data queries, schema discovery, and evidence-backed search.
According to the description, it is designed for table data in Excel and CSV folders. It is not a general writing tool, but for structured table retrieval and querying.
It emphasizes deterministic querying and evidence tracing, not just keyword matching. You can more reliably locate data sources and inspect the corresponding file and row evidence.
Query Excel and CSV data in natural language for fast analysis.
Query CSV and TSV data with natural language and cell-level citations.
Lets AI read messy Excel files and extract clean tabular data.
Query spreadsheets in natural language with auditable, read-only structured analysis.
Turn Excel files into queryable databases for analysis and export.
Read, export, and modify Excel workbooks through MCP efficiently.