Divar Intelligence MCP

dv_similar

Read-onlyIdempotent

Find like-for-like items by rejecting those with different critical specs and explaining exclusions. Optional request parameters narrow the sample.

Instructions

Find like-for-like items; reject unknown/different critical specs and explain exclusions. Optional request narrows the sample.

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": {
      "listing": "<listing>"
    },
    "name": "dv_similar"
  }
}

Input Schema

Name	Required	Description	Default
`listing`	Yes
`request`	No

Output Schema

Name	Required	Default
`data`	Yes
`warnings`	No
`schema_version`	No	1.0

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 19, 2026

TDQS

C2.9/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world behavior. The description adds genuine behavioral context beyond that: it rejects unknown/different critical specs and explains exclusions. However, it doesn't define what a "critical spec" is or how exclusions surface (though the output schema may cover returns).

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?

Two tight sentences, front-loaded with the core purpose and zero filler. Size is appropriate, though the second clause is somewhat cryptic given the complex schema it fronts.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema is complex with a nested SearchRequest, Constraints objects, and many tunable fields at 0% description coverage; two sentences cannot adequately explain how `listing` seeds the comparison or how the request modifiers interact. An output schema exists, so return values needn't be covered, but input completeness is poor.

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 description coverage is 0%, so the description bears full burden. It only characterizes the optional `request` as narrowing the sample and leaves `listing` (the required anchor) and the nested request fields (constraints, strict, verify_details, filters, price bounds) entirely unelaborated.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ("Find like-for-like items") and adds a scoping constraint ("reject unknown/different critical specs"). It is distinguishable from generic search siblings but does not name any specific alternative among the ~30 tools.

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?

"Optional request narrows the sample" hints at how the request arg behaves, but there is no explicit when-to-use versus dv_search, dv_nearby, or dv_compare, and no stated prerequisites or exclusions. The agent must infer the selection criteria from the tool name alone.

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