Skip to main content
Glama
AceDataCloud

mcp-webextrator

by AceDataCloud

webextrator_get_tasks_batch

Retrieve results of multiple previously created extraction or rendering tasks in a single batch request. Supports pagination for large task lists.

Instructions

Retrieve the results of multiple previously created extract or render tasks.

Use this when:
- You submitted multiple async requests and want to check their results together
- You want to paginate through a list of tasks

Returns:
    JSON response containing the list of task statuses and result data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoList of task UUIDs to retrieve in batch.
limitNoPagination limit for batch retrieval, 1-100. Default is 50.
offsetNoPagination offset for batch retrieval. Default is 0.
trace_idsNoList of trace UUIDs to retrieve in batch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries burden. Mentions returns JSON with statuses and result data, but no details on idempotency, rate limits, or side effects. Adequate but not detailed.

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 paragraphs, front-loaded with purpose and usage guidelines. No redundant information.

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?

Given output schema exists and good parameter documentation, description is mostly complete. Could mention that tasks are created by webextrator_extract or webextrator_render, but not essential.

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 coverage is 100% with parameter descriptions. Description adds context on pagination and batch retrieval by IDs/trace_ids, but does not significantly enhance understanding beyond 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?

Clearly states it retrieves results of multiple extract/render tasks, distinguishing from sibling webextrator_get_task which handles single task retrieval.

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?

Explicitly describes when to use: after multiple async requests or for pagination. Lacks explicit 'when not to use' but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AceDataCloud/WebExtratorMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server