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document-mcp

by ExaDev
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TypeScript
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Export one .odb table to CSV

odb_to_csv

Extracts a table from an embedded .odb database and returns it as CSV. Specify the table name when the database contains multiple tables.

Instructions

Extracts exactly one named table from an embedded .odb database as CSV bytes. The table name is required whenever the database declares more than one table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNoThe table to export -- required when the .odb declares more than one table.
outputNoWhere to write the resulting CSV. 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

A4/5.0
Behavior3/5

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

No annotations are provided, and the description does not disclose potential side effects, permissions, or error behavior. It only describes the extraction action, but does not explicitly state whether the operation is read-only or if it modifies the database.

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 a single concise sentence that communicates the core functionality without extraneous details. It is front-loaded with the main action and includes a necessary conditional.

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?

The description, combined with the thorough schema, covers the main functionality and special conditions. It lacks explicit error handling or edge cases, but given the tool's simplicity and the schema's detail, it is sufficiently complete.

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?

The schema provides complete descriptions for all parameters, including nested properties, and the tool description reinforces the requirement for the table parameter when multiple tables exist. The description adds context that ties parameters to the tool's behavior, but most semantic weight is carried by 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 the purpose using the verb 'extracts' and specifies the resource 'exactly one named table from an embedded .odb database', as well as the output format 'CSV'. It distinguishes from sibling tools by focusing on CSV extraction.

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

Usage Guidelines3/5

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

The description provides a conditional usage note ('required whenever the database declares more than one table') but does not explicitly state when to use this tool over alternatives like odb_to_xlsx. It implies a single-table CSV use case but lacks explicit guidance.

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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