Optical Context MCP server

<!-- mcp-name: io.github.ChrBoebel/optical-context-mcp -->

Optical Context MCP

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

Optical Context MCP is built for one specific job: turning large, visually structured PDFs into a smaller set of retrievable packed images for agent workflows.

It reads a local PDF, runs OCR with Mistral, recomposes the extracted text and figures into dense PNGs, and exposes those artifacts over MCP for batch retrieval.

What It Does

• reads a local PDF from the MCP host machine
• extracts page markdown and embedded images with Mistral OCR
• packs that content into dense PNGs that preserve visual grouping
• optionally sizes embedded figures with a bundled technical-document model
• stores a manifest and temp job artifacts for follow-up retrieval
• lets an agent pull only the packed images it needs

Where It Fits

Use it for:

• operating manuals
• scanned handbooks
• product catalogs
• PDF slide decks
• visually structured OCR-heavy documents

Skip it for:

• tiny PDFs
• clean text-native PDFs where normal extraction is enough
• workflows that require exact page-faithful rendering
• cases where OCR cost is not justified

Example Result

The image below shows a real local validation run on a public research paper with dense text, figures, charts, and page-level visual structure. The packed image on the right consolidates the seven source pages shown on the left.

Example local run facts from the generated manifest:

• source paper pages: 22
• previewed source page range: 15 to 21
• extracted images: 30
• packed output images: 6
• example packed image size: 986x1084
• example packed image file size: 536,697 bytes

This example shows the intended workflow: take a long, visually structured PDF and compress it into a smaller set of retrievable packed images that still preserve the visual structure of the source.

Install

python -m pip install optical-context-mcp

Install with the adaptive sizing runtime:

python -m pip install "optical-context-mcp[ml]"

Run without installing:

uvx optical-context-mcp

• MISTRALAPIKEY is required for compress_pdf
• packed images are always stored locally under the system temp directory
• compress_pdf returns up to 30 packed images inline by default
• the adaptive sizing checkpoint is bundled with the package
• adaptive sizing activates automatically when torch and torchvision are available
• set OPTICALCONTEXTDISABLEADAPTIVESIZING=1 to force the legacy fixed sizing
• set OPTICALCONTEXTADAPTIVEMODELPATH=/path/to/model.pt to override the bundled checkpoint

For pinned shared setups:

uvx --from optical-context-mcp==0.1.5 optical-context-mcp

Run

Default transport is stdio:

optical-context-mcp

Claude Code

Register the server in a project:

Shortened. The full README is on GitHub.