Divar Intelligence MCP

dv_count

Read-onlyIdempotent

Retrieve an approximate upstream listing count for Divar searches, and label locally constrained results as sample counts, not source-wide totals.

Instructions

Public upstream approximate count or an explicitly labelled returned-sample count. Local constraints are not a source-wide count.

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": {
      "request": "<request>"
    },
    "name": "dv_count"
  }
}

Input Schema

Name	Required	Description	Default
`request`	Yes

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

C2.4/5.0

Behavior4/5

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

The description discloses that the count is either a public upstream approximation or an explicitly labelled returned-sample count, clarifying the nature of the result beyond the read-only annotations. This is valuable context not covered by structured fields.

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?

The description is two sentences with no wasted words, and the key caveat is front-loaded. However, the phrasing is slightly cryptic, which reduces clarity despite the brevity.

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?

For a tool with a complex nested request object and an output schema, the description is far too sparse. It does not explain how to construct a count query, what fields support counting, or what the output represents.

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

Parameters1/5

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

With 0% schema description coverage, the description must compensate by explaining parameters, but it provides no information about any of the request fields. It fails entirely to add meaning beyond the schema.

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

Purpose2/5

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

The description mentions an 'approximate count' but never states what is being counted (listings, results, etc.). It does not provide a clear verb+resource pair that distinguishes it from siblings like dv_search.

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?

It only warns that 'local constraints are not a source-wide count', which is a limitation, not guidance on when to use this tool versus alternatives. There is no explicit when-to-use or when-not-to-use guidance.

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