# LotAPI

> Use this tool when you need to retrieve detailed property information for US addresses, such as zoning, permit history, and assessed values, to inform real estate, urban planning, or development decisions. The LotAPI tool takes a street address as input and returns relevant data, including zoning, permit history, and neighborhood information, with response codes indicating resolution status. Ideal for applications requiring rapid, deterministic parcel intelligence in major US cities, including San Francisco, Oakland, Boston, and others.

Canonical page: https://skillsregistry.net/skills/lotapi-com-lotapi  
JSON: https://api.skillsregistry.net/v1/skills/lotapi-com-lotapi

## Description

Deterministic parcel intelligence for US properties. Resolves any street address to zoning, permit history, assessed values, planning cases, and neighborhood data. Covers San Francisco, Oakland, Boston, Washington DC, Los Angeles, and New York City. Hard status codes: RESOLVED, NO_MATCH, MULTIPLE_MATCH, DATA_UNAVAILABLE. Sub-200ms on cached addresses. $0.25/call, pay-as-you-go.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** api-integration
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/lotapi-com/lotapi)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "lotapi-com-lotapi"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lotapi-com-lotapi` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lotapi-com-lotapi/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt