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MBaranekTech

PDF RAG MCP Server

by MBaranekTech

pdf_ingest

Ingest PDF files by extracting text (with OCR for scanned pages), splitting into chunks, generating embeddings, and storing them for semantic search.

Instructions

Ingest a PDF file: extract text (with OCR fallback for scanned pages), split into chunks, generate embeddings, and store for search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute path to the PDF file to ingest.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full responsibility for behavioral disclosure. It does well by revealing multi-step behavior, including OCR fallback for scanned pages, chunking, embedding generation, and persistent storage—all meaningful side effects beyond the simple input schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, tightly packed sentence that front-loads the core action and then enumerates the pipeline efficiently. Every clause earns its place with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with an output schema, the description covers the essential workflow: extraction, OCR fallback, chunking, embeddings, and storage. Minor gaps such as file size limits, overwrite behavior, or asynchronous execution are not mentioned, but nothing critical is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully documents the single parameter file_path with a clear description and 100% coverage. The tool description adds no new parameter-level semantics, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Ingest'), a resource ('PDF file'), and the full pipeline (extract text, OCR fallback, chunk, embed, store). This clearly distinguishes it from siblings like pdf_search, pdf_get_page, pdf_delete, and pdf_extract_tables, which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is for adding PDFs to a searchable store, but it never explicitly states when to use it versus alternatives, nor does it name sibling tools or exclusions. An agent must infer the intended context from the sibling list and the word 'for search.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.