Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/sandraschi/ocr-mcp/ocr-expertnpx skills add sandraschi/ocr-mcp --skill ocr-expertgit clone --depth 1 https://github.com/sandraschi/ocr-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sandraschi/ocr-mcp/ocr-expert)<a href="https://agentmods.dev/skills/sandraschi/ocr-mcp/ocr-expert"><img src="https://agentmods.dev/badge/skills/sandraschi/ocr-mcp/ocr-expert.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00504 |
| Opus 5 | $0.00000 | $0.00252 |
| Sonnet 5 | $0.00000 | $0.00101 |
| Haiku 4.5 | $0.00000 | $0.00050 |
Grade A, and why
ocr-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
OCR Expert Skill
You are connected to OCR-MCP, a FastMCP 3.4+ server with 14 OCR backends. This skill teaches you how to use it effectively.
Available Backends (14)
| Backend | Params | VRAM | License | Best For |
|---|---|---|---|---|
| unlimited-ocr | 3B | ~6GB | MIT | Long docs, unbounded parsing |
| paddleocr-vl | 0.9B | 3.3GB | Apache | General docs, tables, 109 langs |
| mineru-2.5 | 1.2B | ~4GB | Apache | Academic/technical docs |
| nemotron-vl | 8B | ~16GB | NV Open | Invoices, forms, charts (EN only) |
| deepseek-ocr2 | 3B | ~8GB | MIT | Structured markdown extraction |
| olmocr-2 | 7B | ~16GB | Apache | Academic PDFs, math |
| mistral-ocr | API | 0 | Cloud | High accuracy cloud OCR |
| got-ocr | 580M | ~2GB | Apache | Fast, lean VRAM |
| tesseract | CPU | 0 | Apache | CPU fallback, always available |
Default backend: unlimited-ocr. Auto-selection falls back through the chain.
Core Workflows
Single document OCR
process_document(operation="process_document", image_path="doc.png", backend="unlimited-ocr")
Scan then OCR
operate_scanner(operation="scan_document", device_id="...", dpi=300)
process_document(operation="process_document", image_path="<result.path>", backend="unlimited-ocr")
Table extraction
process_document(operation="extract_tables", image_path="table.png", backend="paddleocr-vl")
Key Configuration
OCR_DEVICE:cuda(default if GPU),cpuOCR_CACHE_DIR: model download cacheMISTRAL_API_KEY: required for mistral-ocr backendOCR_SAMPLING_USE_CLIENT_LLM=1: use host IDE's LLM instead of local Ollama
Agentic Workflow
For multi-step tasks, use execute_agentic_workflow with a natural language goal.
The agent will autonomously call tools in sequence.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 50 lines · 0 tokens per session scan A ba0b8a3daedb
ocr-expert is a skill published in the GitHub repository sandraschi/ocr-mcp (20 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 504 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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