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kobotoolbox-mcp-server

by OuattaraTech
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TypeScript
Hybrid

List KoboToolbox Form Submissions

kobo_list_submissions
Read-onlyIdempotent

List submitted responses for a form, newest first. Filter by query or paginate to find specific submissions.

Instructions

List submitted responses for a form, most recent first.

Args:

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

  • limit (number): max submissions to return, 1-100 (default 30)

  • offset (number): pagination offset (default 0)

  • query (string, optional): Mongo-style JSON filter, e.g. '{"crop_health":"poor"}'

  • response_format ('markdown' | 'json')

Returns: submission id, submission time, and answered fields for each submission.

Examples:

  • Use when: "Show me the latest 10 responses to my cocoa form" -> uid=..., limit=10

  • Use when: "Which submissions reported poor crop health?" -> query='{"crop_health":"poor"}'

  • Don't use when: you want a downloadable Excel file (use kobo_export_submissions_excel instead)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesAsset uid of the form (from kobo_list_forms)
limitNoMaximum number of submissions to return
queryNoOptional Mongo-style filter query, e.g. '{"farmer_name":"Kouassi"}'
offsetNoNumber of submissions to skip, for pagination
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: most-recent-first ordering, optional Mongo-style query filtering, pagination via offset, and the return shape (submission id, submission time, answered fields). These go beyond the annotations and schema.

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

Conciseness4/5

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

The description is well-structured with Args, Returns, and Examples sections, and the purpose is front-loaded in the first sentence. It is somewhat longer than necessary because the Args block repeats schema descriptions, but the examples and explicit usage guidance earn their place.

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?

With no output schema, the description correctly states the return fields. It also covers ordering, query filtering, pagination, response format, and the main alternative tool. For a read-only list operation with rich annotations, nothing essential is missing for an agent to select and invoke it correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents all five parameters. The description largely duplicates schema information in the Args block, but it adds a practical example for the query parameter ('crop_health':'poor') and the 'latest 10 responses' use case. This gives a baseline-appropriate 3 with only modest added meaning.

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 opens with a specific verb and resource: 'List submitted responses for a form, most recent first.' It distinguishes itself from siblings by being a plural list operation versus kobo_get_submission, and by explicitly contrasting with kobo_export_submissions_excel for downloadable output. The scope is immediately clear.

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?

The description provides explicit 'Use when' examples for two common agent intents and an explicit 'Don't use when' case that names the correct alternative tool. This gives clear selection criteria relative to sibling tools.

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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