OCR.space MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OCR_SPACE_API_KEY | Yes | Free tier API key from OCR.space | |
| OCR_SPACE_PRO_API_KEY | No | Optional PRO tier API key | |
| OCR_SPACE_PRO_ENDPOINT | No | Optional PRO endpoint URL (e.g., https://eu.api.ocr.space/parse/image) | https://api.ocr.space/parse/image |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ocr_fileA | Extract text from a local image or PDF file using OCR.space API. Supports PNG, JPG, GIF, BMP, TIFF, PDF. Free tier: max 1 MB. PRO tier: max 5 MB (EU endpoint for GDPR). Optionally saves result to txt or json file. |
| ocr_urlA | Extract text from an image or PDF at a URL using OCR.space API. The URL must be publicly accessible. Free tier: max 1 MB. PRO tier: max 5 MB. |
| ocr_autoA | Smart OCR that automatically handles oversized files. For PDFs: splits into chunks, OCRs each, and joins results. For images: compresses to fit within size limit before OCR. Use this when you don't know if the file exceeds the size limit. |
| split_pdfA | Split a large PDF into smaller chunks that fit within API size limits. Useful for processing PDFs that exceed the 1 MB (free) or 5 MB (pro) limit. Each chunk contains as many pages as possible while staying under the limit. |
| list_languagesA | List all supported OCR languages with their codes. |
| check_tier_statusA | Check which API tiers are configured and available. Shows which environment variables are set. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool has a distinct purpose: URL-based OCR, file-based OCR, auto-handling of oversized files, PDF splitting, language listing, and tier status check. There is no overlap between these operations.
All tool names follow a consistent snake_case verb_noun pattern (e.g., ocr_url, split_pdf, list_languages). The 'ocr_' prefix for the three OCR variations and clear verbs for helpers make the set easy to predict.
With 6 tools, the server is well-scoped: three OCR methods, one PDF utility, and two informational tools. This is neither too sparse nor overloaded for the domain.
The toolset covers the core OCR lifecycle end-to-end: extracting from URL or file, handling oversized inputs via auto-splitting/compression, splitting PDFs manually, and providing necessary supporting info (languages, tier status). No obvious gaps remain.