# MCP Mistral OCR Optimized

> Use this tool when you need to efficiently extract text and tables from documents using OCR processing, to solve problems such as automating data entry or archiving. It takes local files or URLs as input and outputs structured markdown and HTML formats, minimizing token costs through high-performance batch operations and async connection pooling. Ideal for use cases requiring rapid and cost-effective document processing, such as data migration or digital archiving projects.

Canonical page: https://skillsregistry.net/skills/snussik-mcp-mistral-ocr-opt  
JSON: https://api.skillsregistry.net/v1/skills/snussik-mcp-mistral-ocr-opt

## Description

An optimized Model Context Protocol server for document OCR processing using Mistral AI with support for high-performance batch operations and async connection pooling. It enables efficient extraction of text and tables from local files or URLs into structured markdown and HTML formats while minimizing token costs.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-04-21

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pnfoiuuz0o)
- **Repository:** <https://github.com/snussik/mcp_mistral_ocr_opt>

## 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": "snussik-mcp-mistral-ocr-opt"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/snussik-mcp-mistral-ocr-opt` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/snussik-mcp-mistral-ocr-opt/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
