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document-mcp

by ExaDev
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TypeScript
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Export .odb tables to xlsx

odb_to_xlsx

Convert an embedded .odb database to an xlsx workbook, extracting each table into its own sheet for easy spreadsheet analysis.

Instructions

Extracts every table an embedded .odb database declares into one xlsx workbook, one sheet per table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNoWhere to write the resulting xlsx workbook. Omit entirely (or omit outputPath within it) to receive the bytes inline instead.
sourceYes.odb database to read. 'path' points at the .odb file on disk -- its extension is never used to infer a document format, since documents.js deliberately excludes 'odb' from DocumentFormat (an embedded database front end has no single natural target format -- tables, saved queries, and reports are three unrelated output shapes -- see that package's own README). 'bytesBase64' carries the .odb bytes inline; its 'format' field is required by the shared hybrid input shape but unused by every odb tool.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv2.1.8
    • changedInput schema / properties / source / anyOf
      Previous value: -[
-  {
-    "properties": {
-      "path": {
-        "description": "Filesystem path to the document to read. The document format is inferred from the file extension.",
-        "type": "string"
-      }
-    },
-    "required": [
-      "path"
-    ],
-    "type": "object"
-  },
-  {
-    "properties": {
-      "bytesBase64": {
-        "description": "Base64-encoded document bytes.",
-        "type": "string"
-      },
-      "format": {
-        "description": "The document format of bytesBase64 -- required, since inline bytes carry no filename to infer it from.",
-        "enum": [
-          "docx",
-          "pptx",
-          "xlsx",
-          "odt",
-          "odp",
-          "ods",
-          "odg",
-          "odf",
-          "markdown",
-          "pdf"
-        ],
-        "type": "string"
-      }
-    },
-    "required": [
-      "bytesBase64",
-      "format"
-    ],
-    "type": "object"
-  }
-]New value: +[
+  {
+    "properties": {
+      "path": {
+        "description": "Filesystem path to the document to read. The document format is inferred from the file extension.",
+        "type": "string"
+      }
+    },
+    "required": [
+      "path"
+    ],
+    "type": "object"
+  },
+  {
+    "properties": {
+      "bytesBase64": {
+        "description": "Base64-encoded document bytes.",
+        "type": "string"
+      },
+      "format": {
+        "description": "The document format of bytesBase64 -- required, since inline bytes carry no filename to infer it from.",
+        "enum": [
+          "docx",
+          "pptx",
+          "xlsx",
+          "odt",
+          "odp",
+          "ods",
+          "odg",
+          "svg",
+          "odf",
+          "csv",
+          "markdown",
+          "pdf"
+        ],
+        "type": "string"
+      }
+    },
+    "required": [
+      "bytesBase64",
+      "format"
+    ],
+    "type": "object"
+  }
+]
  2. Addedv1.1.6

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It mentions extraction and output format but doesn't describe side effects, permissions, or edge cases (e.g., behavior with no tables, handling of large files). It adds some value beyond the schema but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one concise sentence that front-loads the purpose and includes the key detail about sheet-per-table. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (nested input, no output schema), the description adequately covers the main transformation. It could mention behavior with missing tables or output naming, but it's reasonably complete for a conversion tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds clarity around the source being an embedded .odb database and output being a workbook with sheets per table. It clarifies that 'format' is unused for odb tools, which is extra context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it extracts every table from an embedded .odb database into one xlsx workbook, one sheet per table. This is specific and distinguishes it from siblings like odb_to_csv or odb_tables.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for exporting .odb tables to xlsx, but doesn't explicitly mention when to use it over alternatives like odb_to_csv or odb_query. However, the output format is clear from the name and description, providing adequate context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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