# fileai-mcp

> Use this tool when you need to automate file processing tasks, such as uploading files, performing Optical Character Recognition (OCR), and extracting structured data from documents. The fileAI MCP Server solves problems related to document classification and data extraction, providing a robust pipeline for working with various file types. It accepts file uploads as input and outputs extracted data and classified documents, making it ideal for use cases involving large-scale document processing and data extraction.

Canonical page: https://skillsregistry.net/skills/fileai-file-ai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/fileai-file-ai-mcp

## Description

The fileAI MCP Server offers a robust set of tools to work with the fileAI file processing pipeline. It allows for uploading files, performing Optical Character Recognition (OCR), classifying documents, and extracting structured data. The server leverages the Model Context Protocol (MCP) to provide

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gkxm486f8b)
- **Repository:** <https://github.com/fileAI/file-ai-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": "fileai-file-ai-mcp"
    }
  }
}
```

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