Skip to main content
Glama
SreeTarak2

DataFlow MCP Server

by SreeTarak2

get_records_for_structuring

Fetch raw scraped contest records and the structuring prompt (v4.0 schema) to prepare data for normalization into the Contests format.

Instructions

Fetch raw scraped records + the structuring prompt (contest-structuring-v4.0.txt, v4.0 schema) so a chatbot can structure them into the normalized Contests format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum raw records to fetch (default 5, max 20)
sourceNoFilter by scraper source (e.g. "contestwatchers"). If None, all sources.
require_validatedNoIf True, only fetch records with validationStatus="validated"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the behavioral burden. It states that it fetches raw records and the prompt, implying a read-only operation. However, it does not mention side effects, authorization, or record readiness for structuring, so some behavioral gaps remain.

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, front-loaded sentence with no fluff. It packs the key elements: action, resource, prompt version, schema version, and target format.

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?

The description covers the essential purpose and identifiers (prompt version, schema, output format). With an output schema present, return values are already defined elsewhere. It could improve by noting when to use this over sibling tools, but it is otherwise complete for a fetch operation.

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%, so parameters are fully described in the schema. The description adds no additional parameter-specific context, thus the baseline score of 3 is appropriate.

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 uses a specific verb ('Fetch') and clearly identifies the resources ('raw scraped records + the structuring prompt'). It differentiates from siblings by mentioning the exact prompt file and 'normalized Contests format', making it distinct from event/validation/similar tools.

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 provides clear context: this is for structuring records into the Contests format. It implies use for structuring workflows but does not explicitly list alternatives or when-not conditions, so it falls just short of a 5.

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/SreeTarak2/dataflow_mcp'

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