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SadaaYogee

Notion MCP Server

by SadaaYogee

Open Page Workbench

notion_open_page_workbench

Open an interactive workbench to read Notion page content, select block IDs, update simple blocks, and append Markdown.

Instructions

Open an interactive Notion Page Workbench MCP App for reading page content, selecting block IDs, updating simple blocks, and appending Markdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoSpecify the response format. 'json' returns the original data structure, 'markdown' returns a more readable format. Use 'markdown' when the user only needs to read the page and isn't planning to write or modify it. Use 'json' when the user needs to read the page with the intention of writing to or modifying it.
page_idNoOptional initial page ID to read.It should be a 32-character string (excluding hyphens) formatted as 8-4-4-4-12 with hyphens (-).
Behavior3/5

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

Annotations already indicate readOnlyHint=false, idempotentHint=false, destructiveHint=false. The description adds that the tool supports reading, selecting, updating, and appending, which aligns with write operations. However, it does not disclose additional behavioral traits such as required permissions, interactive UI behavior, or what happens on failure, making the added value minimal.

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

Conciseness4/5

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

The description is a single concise sentence listing actions, which is easy to parse. It is front-loaded with the main purpose. However, it could be more structured (e.g., bullet points) to separate reading vs. writing capabilities.

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

Completeness2/5

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

Despite no output schema, the tool is described as an interactive workbench, but key details are missing: what the workbench returns, whether it requires further user interaction, and how it differs from using multiple individual tools. For a complex tool combining reading and writing, the description is incomplete.

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 both parameters fully described. The tool description does not add extra parameter-level meaning beyond what the schema already provides; it only lists capabilities generically. Baseline 3 is appropriate.

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 clearly states the tool opens an interactive workbench for reading, selecting, updating, and appending to Notion pages. It uses specific verbs and resource. However, it does not explicitly differentiate this workbench from sibling tools like notion_read_page or notion_append_markdown, which limits full clarity on when to choose this tool over others.

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?

No explicit when-to-use or when-not-to-use guidance relative to sibling tools is provided in the description. The format parameter description gives some indirect guidance (markdown for reading only, json for modification), but the tool-level description lacks contextual comparisons, leaving the agent to infer usage.

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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