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kobotoolbox-mcp-server

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TypeScript
Hybrid

Export KoboToolbox Submissions to Excel

kobo_export_submissions_excel
Read-only

Export all form submissions as a downloadable Excel (.xlsx) or CSV file, and receive the file embedded in the response along with a direct download link.

Instructions

Generate a downloadable Excel (.xlsx) or CSV export of all submissions for a form, and return the file itself (base64-encoded) plus a direct download link.

This triggers a fresh export on the Kobo server, waits (up to ~90s) for it to finish, downloads the result, and returns it as an embedded file the calling app can save to disk.

Args:

  • uid (string): the form's asset uid (from kobo_list_forms)

  • format ('xlsx' | 'csv', default 'xlsx')

  • language (string, optional): label language for the column headers on a multilingual form

Returns: the file as an embedded resource (base64), its size, and a direct download URL as a fallback.

Examples:

  • Use when: "Give me an Excel file of all responses to my cocoa form" -> uid=..., format="xlsx"

  • Don't use when: you just want to read a few submissions in chat (use kobo_list_submissions instead — much faster)

Error Handling:

  • Returns "Error: ... did not complete within 90s" for very large forms — the export may still finish server-side; check the Kobo web UI's export history

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesAsset uid of the form to export submissions from
formatNoExport file formatxlsx
languageNoLabel language for the column headers on a multilingual form (default: the stored codes)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already provide readOnlyHint and destructiveHint, and the description adds meaningful operational context: it triggers a fresh export server-side, waits up to ~90s, downloads the result, and returns it in an embeddable base64 form. The 90s timeout behavior is a key non-obvious trait that the agent needs to know.

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 structured with a clear opening summary followed by Args, Returns, usage examples, and Error Handling. Every section earns its place, the main behavior is front-loaded, and no filler or redundant restatement of the title is present.

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

Completeness5/5

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

For a tool with no output schema, the description fully explains the return value: embedded base64 file, size, and download URL. It also covers the failure mode for large forms and advises checking the Kobo web UI, so an agent can set expectations and recover from timeouts.

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%, so the baseline is 3, but the description adds extra value by telling the agent where to get the uid ('from kobo_list_forms') and clarifying the optional language parameter's effect on multilingual form column headers. These are small but genuinely useful additions 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?

States a specific verb ('Generate... export') and a concrete resource ('all submissions for a form'), with both supported formats named. It also distinguishes the tool from the submission-reading sibling by explicitly saying when not to use it.

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

Usage Guidelines5/5

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

Provides explicit use cases with a concrete example ('Give me an Excel file...') and a clear exclusion ('Don't use when... use kobo_list_submissions instead'). The agent is told both when and when not to invoke this tool, and which alternative to pick.

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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