Log inSubmit server
Landbenchmark MCP logo

Landbenchmark MCP

Checks a parcel with LandBenchmark satellite signals and returns a cited green, caution, or walk-away verdict.

InstallRepositoryWebsite
Full README Compare alternatives Embed widget Claim this listing

Install Landbenchmark MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "landbenchmark-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "landbenchmark-mcp"
      ],
      "env": {
        "TERRAIN_API_KEY": "YOUR_VALUE_HERE",
        "TERRAIN_BASE_URL": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y landbenchmark-mcp

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked Today.

Overview

The landbenchmark-mcp MCP server lets AI agents send parcel coordinates or GeoJSON to LandBenchmark for satellite-based land due diligence. Its single `analyze_parcel` tool evaluates flooding, slope and buildability, soil, hazards, and access, then returns a green, caution, or walk-away result with cited signals. Use it when an agent needs an initial parcel screen based on observed satellite data rather than an unsupported guess. Analyses run in either a shorter lite mode or a deeper multi-year full mode and include a link to the complete report.

Use cases

  • Screen a parcel before deeper land research
  • Compare flooding and buildability signals across parcels
  • Request a multi-year satellite assessment
  • Provide cited land signals in an AI property workflow

Key features

  • Satellite-based parcel due diligence
  • Green, caution, or walk-away verdicts
  • Flooding, slope, soil, hazard, and access signals
  • Point, polygon, and coordinate inputs
  • Lite and full analysis modes
  • Linked full reports

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

7/7 checks healthy over the last 46d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 8d ago via OSV.dev · landbenchmark-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

npm downloads90Package downloads in the last 30 days.
Last commit2mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Landbenchmark MCP works

What landbenchmark-mcp MCP server does

The landbenchmark-mcp MCP server connects an MCP-capable AI client to LandBenchmark, a land-analysis service that uses satellite data for parcel due diligence. It is intended for questions such as whether a parcel appears suitable for further investigation or purchase review. The result is a plain-text assessment containing a verdict, cited signals, and a URL for the full report.

The service evaluates several land-related factors: flooding, slope and buildability, soil, hazards, and access. Its output uses one of three classifications: green, caution, or walk-away. These classifications summarize the available signals; they are not a survey, a formal flood determination, or a replacement for inspection or professional advice.

How it works

An AI agent calls the analyze_parcel tool with either a parcel centre as WGS84 latitude and longitude or a GeoJSON geometry. The geometry can be a point or polygon. An optional label can identify the parcel in the request or resulting report.

The tool supports two analysis modes. lite is the default and typically takes about one minute. full performs a deeper, multi-year satellite analysis and generally takes three to four minutes. The returned summary includes flagged signals and a link to the complete LandBenchmark report.

Setup and configuration

To run the landbenchmark-mcp MCP server, obtain an API key from the API keys section of the LandBenchmark account site. Configure the server as an MCP process launched with npx -y landbenchmark-mcp, then provide both required environment variables:

  • TERRAIN_API_KEY: the LandBenchmark API key.
  • TERRAIN_BASE_URL: the HTTPS base URL for the service, normally https://www.landbenchmark.com.

The base URL is deliberately required rather than assigned a default. Each request sends the API key to that host in an Authorization header. The server rejects plain HTTP destinations except for localhost, which prevents sending the key to an unsecured remote endpoint.

The repository can also be built with npm install followed by npm run build; tests are run with npm test, including a check for the API-key safety guard.

Tools and capabilities

The landbenchmark-mcp MCP server exposes one tool, analyze_parcel. Its supported inputs are:

  • lat and lon: numeric WGS84 coordinates for the parcel centre.
  • geometry: a GeoJSON point or polygon, used instead of coordinates.
  • label: an optional parcel name.
  • mode: lite or full, with lite as the default.

Coordinates or geometry are required as the parcel location. The tool returns the verdict summary as plain text, including the signals that influenced the result and a link to the full report.

Limitations and notes

Results are based on observed satellite data and should be treated as informational. They do not constitute a land survey, flood determination, on-site inspection, or professional advice. The full mode is slower than lite mode, so it is better suited to cases where a deeper multi-year report is worth the additional wait.

The server works with MCP-capable clients, including Claude Desktop and Claude Code. Because it is configured as a standard command-based MCP process, it can also be used with other clients that support stdio MCP servers. The API key and base URL must be configured before startup; the server intentionally refuses to guess the destination host.

Read the full README View source on GitHub

Reviews

No reviews yet — be the first to share how it worked for you.

Frequently Asked Questions about Landbenchmark MCP

landbenchmark-mcp is an MCP server that connects AI agents to LandBenchmark for satellite-based parcel due diligence. Its main tool, `analyze_parcel`, accepts coordinates or GeoJSON and returns a green, caution, or walk-away verdict with cited signals covering flooding, slope and buildability, soil, hazards, and access.

Install it through an MCP client configuration that runs `npx -y landbenchmark-mcp`. Add a LandBenchmark API key as `TERRAIN_API_KEY` and set `TERRAIN_BASE_URL`, usually to `https://www.landbenchmark.com`; both variables are required.

It analyzes either WGS84 `lat` and `lon` coordinates or a GeoJSON point or polygon. You can also provide an optional label and choose `lite` or `full` analysis mode.

Lite analysis usually takes about one minute, while full analysis generally takes three to four minutes. Lite is the default; full produces a deeper multi-year satellite report.

Yes, it works with Claude Desktop. Configure it as a command-based MCP server using `npx`, provide both required environment variables, and then call `analyze_parcel` from the client.

Related MCP servers

All in Aerospace & Astrodynamics All alternatives
Add a badge to your READMEShow it’s listed — live SVG, Markdown or HTML.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:
Live Dynamic SVG PreviewLandbenchmark MCP AllMCPs Directory Badge
Markdown (GitHub README)
[![AllMCPs](https://allmcps.com/api/badge/landbenchmark-mcp?style=directory)](https://allmcps.com/mcp/landbenchmark-mcp)
HTML Embed
<a href="https://allmcps.com/mcp/landbenchmark-mcp"><img src="https://allmcps.com/api/badge/landbenchmark-mcp?style=directory" alt="Landbenchmark MCP on AllMCPs" /></a>