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Jotform MCP Server and API by Cotlet

Read submissions in Jotform

jotform_read_submissions
Read-onlyIdempotent

Read submissions in the user's own Jotform account from ChatGPT, Claude or any AI agent. Returns how to do it in Jotform step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Jotform Cloud Browser. Jotform's official API: Jotform has a full REST API with API keys, and an official hosted MCP server with only 5 tools (checked 17 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "jotform_read_submissions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior4/5

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

Beyond the annotations (readOnly, idempotent, closed-world), the description discloses the crucial behavioral fact that the tool opens nothing and only emits step-by-step UI instructions, plus the dependency on a Cloud Browser session. It does not describe the shape of the returned steps or failure modes, which keeps it below a 5.

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

Conciseness3/5

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

The core two sentences are front-loaded and efficient. The trailing sentence about Jotform's official API and a hosted MCP server with 'only 5 tools (checked 17 Oct 2026)' is promotional aside that does not help the agent invoke the tool correctly.

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

Completeness3/5

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

For a zero-param, no-output-schema tool the description covers what comes back and what to do next, which is adequate. It omits how the target form/submission is determined with no inputs and does not clarify whether the returned steps must then be validated against browser state.

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 tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. It would have helped to note how context (which form/account) is conveyed in the absence of parameters, but that gap is minor.

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

Purpose3/5

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

The name and opening sentence promise 'Read submissions', but the same sentence then reveals the tool 'Returns how to do it in Jotform step by step... and opens nothing by itself' — so it is a guidance tool, not a data reader. The correct purpose is stated, but only after a misleading frame, so an agent may initially expect submission data rather than instructions.

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?

It gives a clear next step ('then do it with the cotlet_browser_* tools in the user's Jotform Cloud Browser'), which is useful routing. However, it never states when to prefer this over the alternatives it mentions (Jotform's REST API or the official hosted MCP server), so the agent is left to infer the selection rule from a dangling comparison.

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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