Paper Reader MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PAPER_READER_CACHE | No | Cache directory. Defaults to %LOCALAPPDATA%\.paper-reader-mcp. | %LOCALAPPDATA%\paper-reader-mcp |
| PAPER_READER_MODELS | No | Offline Docling model directory. | |
| PAPER_READER_OCR_MODE | No | OCR mode: 'auto', 'on', or 'off'. | auto |
| PAPER_READER_TABLE_MODE | No | Table model quality: 'fast' or 'accurate'. | fast |
| PAPER_READER_PDF_PIPELINE | No | PDF pipeline mode: 'standard' or reduced quality fallback 'native'. | standard |
| PAPER_READER_FORMULA_MODEL | No | Formula model: 'off', 'codeformulav2', or 'granite_docling'. | off |
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
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| paper_ingestB | Parse one research file into cached evidence and referenced images. |
| paper_searchC | Return compact, ranked Markdown evidence with page hints and linked image paths. |
| paper_batch_searchC | Retrieve adaptively bounded evidence for up to 32 questions in one MCP call. |
| paper_visualB | Return exactly one relevant extracted image or one on-demand original PDF page/crop. |
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 4 tools
The four tools have distinct primary purposes: ingest parses files, search returns ranked evidence, batch_search handles multiple questions in one call, and visual returns a single image or PDF page. The main potential overlap is between search and batch_search, but the batch version is clearly scoped to multi-question retrieval and bounded evidence. Overall, boundaries are clear.
All names use snake_case with a consistent paper_ prefix. Three tools use a verb (ingest, search, batch_search) while paper_visual is a noun/adjective, slightly breaking the verb_noun pattern. The deviation is minor and the prefix keeps the set predictable.
Four tools is well-scoped for a focused paper reader server. Each tool covers a distinct stage: ingestion, single search, batch search, and visual retrieval. No tool feels redundant or missing at this scale.
The surface covers the core lifecycle: parse a paper, search its evidence, batch search, and fetch visual content. Minor gaps include no tool to list or manage already-ingested papers/cache, and no explicit metadata extraction or full-text retrieval beyond search. These are workable around but prevent full lifecycle coverage.