Homesage.ai MCP

Get Home Value History

get_home_value_history

Read-only

What it returns

A time-series of monthly AVM estimates for a property over the last 5 years. Designed to plot value-over-time charts and detect inflection points (renovation, neighborhood revaluation, market cycle).

When to use it

Render a value-history chart on a property detail page.
Detect properties whose value diverged from their neighborhood trend.

Pricing

1 credit.

FAQ

How far back does the history go?

Up to 60 months. New construction has shorter history. Pre-MLS-era properties may have gaps.

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": {
      "property_address": "<property_address>"
    },
    "name": "get_home_value_history"
  }
}

Input Schema

Name	Required	Description	Default
`property_address`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 3, 2026

TDQS

A4/5.0

Behavior4/5

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

Beyond the annotations, the description discloses meaningful behavioral traits: up to 60 months of history, shorter histories for new construction, possible gaps for pre-MLS-era properties, and a cost of 1 credit. It does not contradict the read-only and non-destructive annotations.

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 front-loaded with return behavior and usage guidance, using headings that make scanning easy. The FAQ section is slightly heavy for a single question, but no sentence is wasted.

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 read-only, single-parameter lookup with an output schema and safety annotations, the description covers purpose, use cases, cost, and data-gap behavior well. The main gap is the lack of address-parameter guidance, which matters given the 0% schema coverage.

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% for the single required property_address parameter. The description only implies that a property is needed and does not explain address formatting, completeness requirements, or validation expectations, so it fails to compensate for the undocumented schema.

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 opens with a specific verb and resource: a time-series of monthly AVM estimates for a property over the last 5 years. It distinguishes this from sibling tools like get_current_estimate by emphasizing historical plotting and inflection-point detection.

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?

It provides an explicit 'When to use it' section with concrete scenarios: rendering a value-history chart and detecting divergence from neighborhood trends. It does not mention when not to use it or name alternative sibling tools for single-point estimates or comps.

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

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