# MCP Quadrant

> Use this tool when you need to efficiently store and search documents with geospatial context, or convert coordinates between different systems like TLC, Plasma, and addresses. The MCP Quadrant enables semantic search with geospatial filtering, allowing for precise retrieval of documents based on location and content. It accepts documents and coordinates as input and returns filtered search results and converted coordinates as output.

Canonical page: https://skillsregistry.net/skills/sakshi-rumsan-mcp-address  
JSON: https://api.skillsregistry.net/v1/skills/sakshi-rumsan-mcp-address

## Description

Enables document storage and semantic search with geospatial filtering using Qdrant, and coordinate conversion between TLC, Plasma, and addresses.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vt766th4cl)
- **Repository:** <https://github.com/sakshi-rumsan/mcp_address>

## 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": "sakshi-rumsan-mcp-address"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sakshi-rumsan-mcp-address` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sakshi-rumsan-mcp-address/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