Skip to main content
Glama
ThinkCol

Lenx MCP Server

by ThinkCol

lenx_get_task_data

Get paginated social media post data for a task within a time range, with cursor-based pagination for large result sets.

Instructions

Retrieve paginated social media post data for a specific task within a time range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesTask ID
fromYesStart unix timestamp (inclusive)
toYesEnd unix timestamp (inclusive)
sizeYesNumber of posts per page (max: 1000)
search_afterNoCursor for pagination: pass the last post's unix_timestamp to get the next page
Behavior2/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. While 'retrieve' implies a read-only operation, it does not explicitly state side effects, auth requirements, or rate limits. No pagination behavior beyond the one-word mention is explained.

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 a single, concise sentence (12 words) that front-loads the key purpose: retrieving paginated social media post data for a specific task within a time range. No extraneous words.

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?

The description covers the basic purpose but is missing details like response structure (no output schema), pagination mechanics (though schema explains search_after), and when to use. It is adequate for a simple retrieval tool but not richly complete.

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?

The input schema has 100% description coverage, so the schema already explains all parameters (task_id, from, to, size, search_after). The description adds no additional parameter semantics, so it scores the baseline 3.

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 verb 'retrieve' and the resource 'social media post data' with specific constraints: pagination, specific task, and time range. It effectively distinguishes from sibling tools like lenx_get_task (likely task metadata) and lenx_list_tasks (list tasks).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus its siblings (e.g., lenx_get_task, lenx_export_task_data). The description does not mention prerequisites, limitations, or alternatives, which is a significant gap given the multiple sibling tools.

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/ThinkCol/lenx-mcp'

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