blinkit-mcp

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blinkit_pick_best

Searches Blinkit for a product, then automatically selects the best option by scoring brand, attributes, availability, and price, including cheaper alternatives when available.

Instructions

Search and auto-pick the best product using the multi-factor scorer (brand + attributes + availability + price), with cheaper-equivalent swap. Returns the chosen product, alternatives, and the reason.

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": {
      "query": "<query>"
    },
    "name": "blinkit_pick_best"
  }
}

Input Schema

Name	Required	Description
`attrs`	No	required attribute keywords, e.g. ['full cream']
`query`	Yes
`brands`	No	preferred brands, best first
`max_price`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 7, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Describes high-level behavior (auto-pick, scorer, swap) but lacks details on the algorithm, failure modes, or side effects. With no annotations, more depth would be beneficial.

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

Conciseness4/5

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

Single sentence covering key points. Could be split for readability, but information density is appropriate.

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?

Describes inputs and outputs (chosen product, alternatives, reason) but lacks details on error handling, edge cases, or success criteria. Adequate but not comprehensive for a complex tool without output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%, and the description adds minimal meaning beyond the schema. While 'brands' and 'attrs' are hinted, the description does not specify how they are used in scoring or provide examples.

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 the tool searches and auto-picks the best product using a multi-factor scorer, with cheaper-equivalent swap. It returns the chosen product, alternatives, and reason, distinguishing it from sibling search tools.

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?

Implies usage for auto-picking but does not explicitly state when to use or not use this tool versus alternatives like blinkit_search. No comparison or conditions provided.

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