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notion-plus-mcp-server

notion-plus-mcp-server

by katekruger
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Get Database Schema

notion_get_schema
Read-onlyIdempotent

Read a Notion database's properties, types, and select or status options before writing, so property values match the schema exactly.

Instructions

Read a database's properties: names, types, select/status options (with status groups), relation targets, and which are read-only. Read this before writing properties so values match exactly.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "database": "<database>"
    },
    "name": "notion_get_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
databaseYesDatabase URL/id or data source id.
data_source_nameNoOnly needed if the database has several data sources.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower. The description adds real value beyond them by disclosing the shape of the result, including status groups and which properties are read-only, plus the dependency on write operations. No pagination or error behavior is mentioned.

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, no filler. The content it returns is listed first and the operational reason to call it is front-loaded as the closing admonition.

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?

With no output schema, the description usefully enumerates the fields returned and the write-prerequisite workflow. It is close to complete for a two-parameter read tool, though it omits any mention of multi-data-source ambiguity resolution beyond what the schema's data_source_name already implies.

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 both parameters (database, data_source_name) are fully documented in the schema itself. The description adds no syntax, format, or selection guidance for them, so the baseline of 3 applies.

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?

States a specific verb ('Read') and resource ('a database's properties') and enumerates exactly what the read returns: names, types, select/status options, status groups, relation targets, and read-only flags. It is not differentiated from the similarly-named sibling notion_schema, which is the only gap.

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?

Gives explicit just-in-time guidance: 'Read this before writing properties so values match exactly.' That tells the agent both when to call it and why. No exclusion or alternative tool is named, so it stops short of a 5.

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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