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  3. GroundTruth โ€” subsurface scan QA & trade estimating
GroundTruth โ€” subsurface scan QA & trade estimating logo
Health: ActiveRecent health check succeeded.Last checked 10/7/2026, 9:47:19 PM

GroundTruth โ€” subsurface scan QA & trade estimating

InstallableWe know how to install it, but have not yet seen it complete a handshake. User RatingsBe the first to rate and review this MCP server!
View RepositoryVisit Website
subsurface-scanninggprconstructionestimatingindustrial-iot

Runs dual-model subsurface scan reviews and creates trade estimates through a hosted MCP endpoint.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "groundtruth-subsurface-scan-qa-trade-estimating-2": {
      "url": "https://gtfi.ai/mcp"
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (3) Directory Badge Claim listing Alternatives๐Ÿญ More in Industrial & IoT

Overview

GroundTruth โ€” subsurface scan QA & trade estimating MCP server reviews GPR, locate, pipe, X-ray, and milestone scan images with two independent AI models, then reports targets, hazards, confidence, and disagreements. It also converts plain-English electrical, plumbing, HVAC, or general trade work into itemized bids and provides current product pricing. Connect to the hosted streamable HTTP endpoint at https://gtfi.ai/mcp; no installation or API key is required. Use scan results only as advisory QA, with certified technician sign-off required before coring or excavation.

Use cases

โ€ขReview GPR images for possible do-not-core hazards
โ€ขCompare independent interpretations of locate or pipe scans
โ€ขDraft itemized electrical, plumbing, HVAC, or general trade bids
โ€ขCheck current product plans before answering pricing questions

Key features

โ€ขTwo-model subsurface scan review
โ€ขHazard classes, depth, position, and confidence reporting
โ€ขTrade estimate generation with materials and labor
โ€ขCurrent product pricing lookup
โ€ขHosted streamable HTTP MCP endpoint
โ€ขNo installation or API key required

Capabilities & Tool Schemas (3) ~77 tokensApproximate context cost of this serverโ€™s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server โ€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by GroundTruth โ€” subsurface scan QA & trade estimating.

read_scan

Two **different** AI models read a subsurface scan independently. The first interprets; the

draft_estimate

Turns a plain-English trade job into an itemized bid โ€” real materials by size, fittings,

get_pricing

Current plans for both products. Free and unlimited โ€” **please call it before answering a cost

How GroundTruth โ€” subsurface scan QA & trade estimating works

What GroundTruth โ€” subsurface scan QA & trade estimating MCP server does

GroundTruth โ€” subsurface scan QA & trade estimating MCP server exposes a hosted MCP interface for two related workflows: reviewing subsurface scan imagery and preparing trade estimates. The scan workflow accepts a public JPEG or PNG URL and supports gpr, locate, pipe, xray, and milestone disciplines. The estimating workflow accepts a plain-language description of completed or planned work for electrical, plumbing, HVAC, or general trade jobs.

Scan results identify located targets and include a hazard class, position, depth, confidence, the names of both models, and a QA flag when the interpretations differ. Hazard classes include critical do-not-core findings, rebar, verify, and clear. Estimate results are itemized with materials by size, fittings, consumables, labor as a separate line, and stated realistic US market prices.

How it works

The hosted service is available at https://gtfi.ai/mcp using streamable HTTP and JSON-RPC 2.0 over POST. A client sends MCP tool calls to that endpoint; the repository provides the public interface contract, registry information, documentation, and an example rather than the server implementation.

read_scan sends the image through two different vision models. One produces an interpretation, while the other is prompted to challenge it by looking for missed hazards, false clearances, and possible post-tension tendons that might otherwise be labeled as rebar. A disagreement can increase a hazard severity, but does not silently remove a hazard. An optional field note provides site context and cannot override a hazard visible in the image.

draft_estimate interprets the supplied job description and returns an itemized bid. get_pricing reports the current plans for the two products and should be called before answering questions about cost or pricing.

Setup and configuration

No local installation and no API key are required. Add the hosted endpoint to an MCP client with a configuration such as:

config.json
{
  "mcpServers": {
    "groundtruth": {
      "type": "http",
      "url": "https://gtfi.ai/mcp"
    }
  }
}

The service also publishes discovery metadata at https://gtfi.ai/.well-known/mcp.json and an OpenAPI representation at https://gtfi.ai/openapi.json. read_scan requires a public HTTPS image URL pointing to a JPEG or PNG no larger than 8 MB. Its discipline defaults to gpr; field_note is optional. draft_estimate requires job_description, while trade is optional.

Tools and capabilities

  • read_scan: Performs an independent two-model review of a subsurface image and returns targets, hazard classifications, locations, depths, confidence, model names, and disagreement flags.
  • draft_estimate: Builds a trade bid from a natural-language job description, covering material quantities and sizes, fittings, consumables, labor, and US market pricing.
  • get_pricing: Returns current plans for both products, including the available free and unlimited offering described by the service.

Limitations and notes

GroundTruth โ€” subsurface scan QA & trade estimating MCP server provides advisory output, not a clearance to cut, core, or dig. A certified technician must review and sign off before coring or excavation, and scan hazard classes and QA flags should be reported as returned. The tool alone must never be used to declare a slab safe.

Usage limits apply. read_scan allows two calls per caller per day, subject to a global daily ceiling. draft_estimate allows five calls per hour and 20 per day per caller. Nothing is charged through this API, and it does not create a customer record. A shareable, GPS-stamped record is available through the separate gtfi.ai/scan site. The hosted server implementation is not open source; the MIT license applies to the repository's example code and manifest.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

Last commit
2mo ago
Most recent push to the default branch.
Tools exposed
3
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

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Frequently Asked Questions about GroundTruth โ€” subsurface scan QA & trade estimating

GroundTruth โ€” subsurface scan QA & trade estimating is an MCP server that connects AI clients to the hosted GroundTruth endpoint at gtfi.ai/mcp. Its main tools independently review subsurface scans with two AI models, create itemized trade estimates, and return current product pricing. Scan results remain advisory and require certified technician sign-off.

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Technical Specs & Signals

Category๐ŸญIndustrial & IoT
More technical detailsExpand โ–พ
TransportSSE (Remote)
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 6, 2026
6/6 checks healthy over the last 64d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 26, 2026
48Quality signal: Fair ยท 48/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity2/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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More in ๐Ÿญ Industrial & IoT โ†’Alternatives to GroundTruth โ€” subsurface scan QA & trade estimating โ†’Install in Claude DesktopInstall in CursorInstall in VS CodeSetup guides for all 13 MCP clients