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dat-ai-mcp

dat-ai-mcp

by willtholke
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

dat_browse_status

Check the status of an async browsing task. Returns status updates and the result once completed.

Instructions

Check the status of an async dat.ai browsing task. Returns status (queued/assigned/running/completed/failed) and result if ready.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>"
    },
    "name": "dat_browse_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
task_idYesThe task_id returned from dat_browse with async=true.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

No annotations provided; description covers return values and statuses but omits idempotency, rate limits, or whether results are consumed. For a simple status checker, this is acceptable but not comprehensive.

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?

Two concise sentences, no fluff. Front-loaded with verb and resource, then details. Every sentence adds value.

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?

For a single-parameter, no-output-schema tool, the description covers purpose, usage context, and return types. Minor gaps like polling behavior or error handling exist but are not critical given tool simplicity.

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?

With 100% schema description coverage, the description reinforces the schema but adds little new semantic meaning. It echoes the schema's mention of async=true context, but does not elaborate on format or constraints.

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 tool checks status of an async browsing task and lists possible statuses, distinguishing it from sibling tools like dat_browse (initiates) and dat_transcribe_status (for transcription).

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 notes the task_id comes from dat_browse with async=true, providing a usage hint. However, it does not explicitly state when not to use or compare to other status tools like dat_transcribe_status.

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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