# @parserelay/mcp

> Use this tool when you need to extract structured data from documents with accuracy, as it parses documents into confidence-scored fields through a scan tool, compatible with MCP hosts like Claude Desktop or Cursor. It solves data extraction problems by providing a reliable and efficient way to convert unstructured document data into usable information. Ideal for use cases requiring automated data processing and integration with MCP systems.

Canonical page: https://skillsregistry.net/skills/parserelay-mcp  
JSON: https://api.skillsregistry.net/v1/skills/parserelay-mcp

## Description

Enables document parsing into structured, confidence-scored fields via the scan tool, working with any MCP host like Claude Desktop or Cursor.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fu0f98vr3a)
- **Repository:** <https://github.com/parserelay/mcp>

## 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": "parserelay-mcp"
    }
  }
}
```

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