Markdown by mdedit.ai

Read a Markdown Document

read_article

Read-onlyIdempotent

Read the current saved Markdown content and metadata for a document. Accepts natural workspace names and document titles; internal identifiers are optional.

Input Schema

TableJSON Schema

Name	Required	Description
`articleId`	No	Internal document identifier when already available. Omit it when the user referred to the document by title.
`workspaceId`	No	Internal workspace identifier when already available. Omit it when the user referred to a workspace by name or has only one workspace.
`articleTitle`	No	Human-visible document title. Prefer this over asking the user for an internal document identifier.
`workspaceName`	No	Human-visible workspace name. Prefer this over asking the user for an internal workspace identifier.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`title`	No
`content`	Yes
`folderId`	No
`isPinned`	No
`articleId`	Yes
`createdAt`	No
`editorUrl`	No
`updatedAt`	No
`isArchived`	No
`contentHash`	Yes
`workspaceId`	Yes
`collaborative`	No

Schema Changelog

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

First observedAug 28, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, covering the safety profile. The description adds the 'current saved' framing and optional-identifier input behavior, but not much behavioral context beyond what annotations and the output schema provide.

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?

Two sentences, with the operation and target front-loaded and the key input flexibility stated second. There is no filler or repetition of structured fields.

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?

Four optional parameters are fully documented, annotations cover safety and idempotency, and an output schema exists, so the essential calling information is present. Naming the closest alternative sibling, such as render_article, would make it slightly more complete, but nothing critical is missing.

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 coverage is 100% and each parameter already has thorough guidance, such as 'Prefer this over asking...' and 'Omit it when...'. The description's summary about natural names and optional internal identifiers is useful but does not add meaning beyond the schema.

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

Purpose4/5

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

The description names a specific operation (reading) and a specific resource ('current saved Markdown content and metadata for a document'), so an agent can tell what the tool does. It does not explicitly distinguish this from siblings like render_article, but the verb and resource are clear enough.

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 gives a clear usage cue: it accepts natural workspace names and document titles, with internal identifiers optional. It stops short of naming alternatives or stating when not to use this tool, so it lacks full exclusion guidance.

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

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TDQS

A3.6/5.0

Disambiguation4/5

Most tools have clearly distinct purposes across article CRUD, review workflows, publishing, and conversion/export. Minor confusion can arise between convert_document and start_article_export (and their corresponding status checkers), but the descriptions explicitly differentiate arbitrary content conversion from exporting stored documents. The render_article tool's broad contextual wording overlaps conceptually with several actions, though its actual function (opening the reader) is unique.

Naming Consistency5/5

All 22 tool names follow a strict snake_case verb_noun pattern, such as list_articles, accept_suggestion, start_article_export, and unpublish_article. There are no mixed conventions, vague verbs, or camelCase outliers, making the naming highly predictable.

Tool Count3/5

At 22 tools, the server sits above the ideal 3-15 range and feels somewhat heavy for an MCP surface. The inclusion of record_article_app_event, a component-only telemetry tool with no agent-facing value, adds to this heaviness. However, the breadth of the domain—documents, collaboration, publishing, and conversion—largely justifies the count.

Completeness3/5

The tool surface covers article lifecycle, review threads, publishing, export/conversion, and presence well, covering most common workflows. A notable gap is the lack of any delete_article or trash operation, leaving no way to remove documents. Additionally, updates are limited to anchored edits via edit_article, with no direct full-content replacement option.

Resources

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