# UrbanPlannerMCP

> UrbanPlannerMCP — salog0d-urbanplannermcp. Use this tool when you need to integrate AI components with urban and environmental datasets, or when accessing structured data through a FastAPI backend is required. It solves problems related to data communication and accessibility between AI pipelines and backend systems. The UrbanPlannerMCP tool takes in dataset requests and outputs structured data, ideal for use cases involving data-intensive urban planning and environmental analysis.

Canonical page: https://skillsregistry.net/skills/salog0d-urbanplannermcp  
JSON: https://api.skillsregistry.net/v1/skills/salog0d-urbanplannermcp

## Description

Acts as the communication layer between the AI components and the FastAPI backend. It exposes the platform’s urban and environmental datasets as structured tools that can be accessed by the LangChain–Gemini–LangGraph pipeline.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/salog0d/UrbanPlannerMCP)

## 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": "salog0d-urbanplannermcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/salog0d-urbanplannermcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/salog0d-urbanplannermcp/pull`

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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