PDF RAG MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pdf_ingestA | Ingest a PDF file: extract text (with OCR fallback for scanned pages), split into chunks, generate embeddings, and store for search. |
| pdf_searchA | Semantic search across all ingested PDFs. Returns the most relevant text chunks ranked by similarity. |
| pdf_get_pageA | Get the full extracted text for a specific page of an ingested PDF. |
| pdf_list_documentsA | List all ingested PDF documents with their metadata. Returns: List of documents with doc_id, filename, page count, chunk count, and ingest date. |
| pdf_deleteA | Remove an ingested PDF and all its embeddings from the store. |
| pdf_extract_tablesA | Extract tables from a specific page of a PDF and return them as markdown. |
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 targets a distinct operation: ingest, search, page retrieval, table extraction, listing, and deletion. There is no meaningful overlap between tool purposes, so an agent can clearly select the right tool.
All tools follow a consistent pdf_ prefix with verb-first naming, such as pdf_ingest, pdf_search, and pdf_get_page. The pattern is predictable and uniformly snake_case throughout.
Six tools is well-scoped for a PDF RAG server, covering ingestion, retrieval, and document management without unnecessary redundancy. Each tool earns its place in the set.
The tool surface covers the full PDF RAG lifecycle: ingest, search, retrieve page context, extract tables, list documents, and delete. There are no obvious dead ends or missing core operations for the stated purpose.