Optical Context MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MISTRAL_API_KEY | Yes | API key for Mistral OCR (required for compress_pdf) | |
| OPTICAL_CONTEXT_ADAPTIVE_MODEL_PATH | No | Override path to the bundled adaptive sizing model checkpoint | |
| OPTICAL_CONTEXT_DISABLE_ADAPTIVE_SIZING | No | Set to '1' to force legacy fixed sizing instead of adaptive sizing |
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": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| compress_pdfC | Read a local PDF, run Mistral OCR, recompose it into dense packed PNG images, and create a retrievable compression job. |
| get_job_manifestC | Load the saved manifest for a previously compressed PDF job. |
| get_packed_imagesC | Return one or more previously generated packed PNG images for a stored job. |
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 3 tools
Each tool has a distinct purpose: compress_pdf initiates processing, get_job_manifest retrieves metadata, and get_packed_images fetches image outputs. The verbs and objects clearly differentiate them.
All tools follow a consistent verb_noun pattern (compress_pdf, get_job_manifest, get_packed_images) with snake_case, using standard verbs like 'compress' and 'get'.
With only 3 tools, the set is minimal but covers the core lifecycle. However, it feels thin for a server that performs OCR, compression, and job management; additional tools like listing jobs or deleting outputs might be expected.
The tools cover creating a compression job, retrieving its manifest, and fetching packed images. Notable gaps include no tool to list all jobs, check job status, or delete a job, which limits lifecycle management.