Skip to main content
Glama
Sign In

Datafiniti

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Datafiniti Property Search

datafiniti_property_search
Read-onlyIdempotent

Search Datafiniti's US property database (100M+ records) — returns address, square footage, bed/bath counts, property type, ownership (people), and tax/assessment data. Uses the Datafiniti field:value query language. Example: datafiniti_property_search({ query: "country:US AND city:"Austin" AND numBedroom:3", num_records: 5, _apiKey: "your-token" })

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "country:US AND province:TX AND city:\"Austin\" AND numBedroom:3",
      "_apiKey": "your-datafiniti-api-key",
      "num_records": 10
    },
    "name": "datafiniti_property_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesDatafiniti query, e.g. `country:US AND province:TX AND city:"Austin"`. Fields: country, province, city, postalCode, propertyType, numBedroom, numBathroom, address.
_apiKeyYesDatafiniti API token (from https://portal.datafiniti.co/). Sent as Authorization: Bearer.
num_recordsNoMax records to return (default 10, set 0 to get only num_found at no credit cost).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive behavior. The description adds valuable context beyond annotations: it mentions the Datafiniti query language, the credit-free behavior of num_records=0, the Authorization header for the API key, and the return data fields. This helps the agent understand side effects (cost) and usage nuances without contradicting the annotations.

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 sentence plus a concrete example. It front-loads the core purpose and immediately illustrates usage, with no filler. Every clause earns its place, and the example makes the syntax concrete without bloating the text.

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?

For a tool with no output schema, the description covers the key return fields, explains the query format, and notes the special num_records=0 behavior. It also states the API key requirement. It does not mention error handling, rate limits, or pagination, but given the tool's moderate complexity and annotation coverage, the description is sufficiently complete for correct invocation.

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 all parameters are already documented. The description restates the query language and provides an inline example, but this largely duplicates the schema examples. It adds minimal new meaning, so the baseline 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 states a specific verb ('Search') and a specific resource (Datafiniti's US property database with 100M+ records). It enumerates the return fields (address, square footage, bed/bath, etc.), and the example query makes the purpose unmistakable. The sibling tools (business/product search) are clearly distinct by domain, so no ambiguity remains.

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?

The description implicitly defines its use case via the property database focus, but it does not explicitly mention alternatives (like datafiniti_business_search) or state when NOT to use it. There is no comparison or exclusion, so an agent must infer appropriateness from the domain alone. This is adequate but not explicit.

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

All Datafiniti toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources