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winds3753

landbenchmark-mcp

by winds3753
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landbenchmark-mcp

An MCP server that lets AI agents run satellite land due-diligence through LandBenchmark. It exposes one tool, analyze_parcel, that returns a green / caution / walk-away verdict with cited signals (flooding, slope & buildability, soil, hazards, access) for any parcel.

Why

When someone asks their AI assistant "is this land any good to buy?", the agent can call LandBenchmark and answer with observed, cited satellite data instead of guessing.

Related MCP server: townshipamerica-mcp

Setup

  1. Get an API key at landbenchmark.com/account → API keys.

  2. Add the server to your MCP client config:

{
  "mcpServers": {
    "terrain": {
      "command": "npx",
      "args": ["-y", "landbenchmark-mcp"],
      "env": {
        "TERRAIN_API_KEY": "tk_live_...",
        "TERRAIN_BASE_URL": "https://www.landbenchmark.com"
      }
    }
  }
}

Both env vars are required. (TERRAIN_* is the internal engine name — LandBenchmark runs on the Terrain analysis engine.) TERRAIN_BASE_URL has no default on purpose: every request sends your API key to that host in an Authorization header, so the server refuses to start rather than guess where it goes. It also refuses to send a key over plain http:// to anything but localhost.

Works with any MCP-capable client — Claude Desktop, Claude Code, and agent frameworks.

Tool: analyze_parcel

Param

Type

Notes

lat, lon

number

Parcel centre (WGS84). Provide these or geometry.

geometry

GeoJSON

Polygon or Point (alternative to lat/lon).

label

string

Optional parcel name.

mode

"lite" | "full"

lite (default) ≈ 1 min; full = deep multi-year satellite report ≈ 3–4 min.

Returns a plain-text verdict summary with the flagged signals and a link to the full report.

Build

npm install
npm run build   # → dist/index.js
npm test        # verifies the API-key safety guard

Links

Informational only — not a survey, flood determination, or a substitute for on-site inspection and professional advice.

Available Tools

1 tool
analyze_parcelA

Run a satellite land due-diligence analysis on a parcel of land and return a green / caution / walk-away verdict plus cited signals (flooding, slope & buildability, soil, hazards like wildfire/seismic/contamination, access, and neighbouring land use). Use when a user is evaluating rural/vacant land to buy. Provide a latitude and longitude (the parcel centre), or a GeoJSON geometry.

ParametersJSON Schema
NameRequiredDescriptionDefault
latNoLatitude of the parcel (WGS84).
lonNoLongitude of the parcel (WGS84).
modeNolite = fast open-data + satellite flood-history scan (~1 min, default); full = deep multi-year satellite report (~3-4 min).
labelNoOptional name for the parcel.
geometryNoGeoJSON Polygon or Point (alternative to lat/lon).

TDQS

A3.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose whether the tool is read-only, whether it modifies data, or any prerequisites like authentication. The behavioral traits are limited to listing returned signals.

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 concise with two sentences. The first sentence immediately states the purpose and output, front-loading critical information. No wasted words.

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?

While the description lists the signals and verdict type, it lacks details on the return structure (e.g., JSON format), error handling, or what happens if neither lat/lon nor geometry is provided. No output schema exists to fill the gap.

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

Parameters4/5

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

Schema coverage is 100%, and the description adds meaningful context: explains that lat/lon represent the parcel centre and that mode options have different run times and data sources. This goes beyond the schema descriptions.

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 clearly states the tool performs satellite land due-diligence analysis and returns a verdict with specific signals like flooding, slope, and hazards. It identifies the exact use case (rural/vacant land evaluation) and output format.

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?

Explicitly states when to use: 'Use when a user is evaluating rural/vacant land to buy.' No alternatives or exclusions are needed as there are no sibling tools, but the guidance is clear and actionable.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.0
    • First observedanalyze_parcel
Install Server
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TDQS

A4/5.0
Disambiguation5/5

There is only one tool, so an agent cannot confuse it with another. No ambiguity exists.

Naming Consistency5/5

With a single tool, naming is trivially consistent. The name 'analyze_parcel' is clear and follows a verb_noun pattern.

Tool Count3/5

One tool is borderline thin for typical server scopes, but it serves a specific analysis purpose. The count is acceptable but feels minimal.

Completeness4/5

The tool covers a broad set of due-diligence signals (flooding, slope, soil, hazards, access, land use) in a single call. Missing batch or persistence features, but the core analysis is comprehensive.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Resources

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