Skip to main content
Glama

read_pdf

Extract text content and metadata from PDF files using the MCP PDF Reader tool. Supports local files and URLs for document analysis.

Instructions

Read and extract text content from a PDF file. Returns the full text content and metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute or relative path to the PDF file, or a URL (http:// or https://)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions returning 'full text content and metadata', which is useful, but lacks details on error handling (e.g., invalid paths, corrupted files), performance (e.g., large file handling), or limitations (e.g., OCR support, encrypted files). The description adds some value but is incomplete for behavioral context.

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?

The description is two sentences with zero waste, front-loaded with the core purpose and efficiently states the return values. Every sentence earns its place by conveying essential information without redundancy.

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

Completeness3/5

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

Given no annotations and no output schema, the description is moderately complete for a simple read operation. It covers the purpose and return values, but lacks details on behavioral traits (e.g., errors, limits) and output structure. It is adequate but has clear gaps in context.

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?

Schema description coverage is 100%, with the parameter 'path' fully documented in the schema. The description does not add any additional meaning beyond what the schema provides (e.g., no examples of path formats or URL specifics). Baseline 3 is appropriate as the schema handles parameter documentation.

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 clearly states the specific action ('read and extract text content') and resource ('from a PDF file'), distinguishing it from sibling tools like 'get_pdf_metadata' (metadata only), 'read_pdf_page' (single page), and 'search_pdf' (search within content). It explicitly mentions both text extraction and metadata return.

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

Usage Guidelines3/5

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

The description implies usage for extracting full text and metadata from PDFs, but does not explicitly state when to use this tool versus alternatives like 'read_pdf_page' for single pages or 'search_pdf' for searching. No exclusions or prerequisites are mentioned.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Saqib-Aziz007/mcp-pdf-reader'

If you have feedback or need assistance with the MCP directory API, please join our Discord server