Skip to main content
Glama

Export Docling document to markdown format

export_docling_document_to_markdown
Read-only

Convert a cached Docling document into markdown format using its unique document key, making it ready for display or further processing.

Instructions

Export a document from the local document cache to markdown format.

This tool converts a Docling document that exists in the local cache into a markdown formatted string, which can be used for display or further processing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_sizeNoThe maximum number of characters to return.
document_keyYesThe unique identifier of the document in the local cache.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
markdownYes
document_keyYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it converts a cached document into a markdown string, but does not disclose behavior around max_size truncation, error cases, or any edge conditions. This is adequate but not rich.

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 concise sentences with no waste. The core action is front-loaded in the first sentence, and the second sentence clarifies the source, output format, and intended use.

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

Completeness5/5

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

For a simple read-only conversion tool with two parameters, full schema coverage, and an output schema, the description is complete enough. It specifies the required precondition ('exists in the local cache'), the output type, and the purpose.

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%, so the schema already documents both document_key and max_size. The description reinforces the local-cache context but adds no meaning beyond the schema, so the baseline of 3 applies.

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 states a specific action ('Export'/'converts') on a specific resource ('Docling document from the local document cache') with a concrete output format ('markdown formatted string'). This clearly distinguishes it from sibling tools like save_docling_document or get_text_of_document_item_at_anchor.

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

Usage Guidelines4/5

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

The description makes the context clear: the document must already exist in the local cache before this tool can convert it, and the resulting markdown string is intended for display or further processing. It does not explicitly name alternatives or exclusions, but the usage context is well implied.

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

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/docling-project/docling-mcp'

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