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kimata1007

notion-ops-mcp

by kimata1007
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.2.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one reads/fetches documents, the other creates or updates them. There is no overlap or ambiguity in their intended use.

    Naming Consistency5/5

    Both tool names follow the exact same pattern: a 'notion_' prefix, a verb ('read' or 'publish'), and an object ('document'). The naming is perfectly consistent and predictable.

    Tool Count3/5

    With only two tools, the server feels thin for the 'notion-ops' scope. However, each tool is broad and capable (bulk reads, conflict-safe writes), so it is borderline rather than severely underdeveloped.

    Completeness4/5

    The read and publish tools together cover searching/resolving, reading, creating, and updating documents, which covers most core workflows. The main gap is the lack of an explicit delete operation, but this is a minor omission given the server's apparent focus on content operations.

  • Average 4.2/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 41 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior4/5

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

    Annotations already indicate destructive and non-read-only behavior. The description adds valuable context about conflict-safe edits, bounded rebasing, and post-write verification, which goes beyond the annotations and helps the agent understand the tool's behavior.

    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 a single, dense sentence that packs in the core functionality and key behaviors. Every word adds value, with no wasted fluff.

    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?

    Given the tool's high complexity (multiple modes, conflict policies, operations), the description covers the main scenarios and safety features. It relies on the schema for detailed parameter structure, which is appropriate since no output schema exists.

    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 56%, and the description doesn't detail parameter meanings. It provides a high-level overview but relies on the schema for specifics. Since coverage is moderate, the description adds some context but doesn't fully compensate for undocumented parameters.

    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 tool creates one or more Notion documents or applies edits to a document. It specifies the write nature and distinguishes itself from the sibling notion_read_document by focusing on creation and editing rather than reading.

    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 implies usage for writing/creating Notion documents, making it clear when to use this tool over the read-only sibling. However, it doesn't explicitly mention when not to use it or provide alternative tool references, so it falls 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.

  • Behavior4/5

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

    The description adds behavioral detail beyond the annotations by specifying the output format ('Markdown and revisions') and the batch capability ('up to eight'). It also notes that search must be 'unambiguous', giving insight into potential failure conditions.

    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 a single, well-structured sentence that front-loads the core purpose ('Resolve and fetch') and packs in key constraints (ID, URL, or search; up to eight pages; output format). There is no wasted text.

    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?

    Given no output schema and moderate complexity, the description appropriately covers the return type ('Markdown and revisions') and the number of documents. It does not mention handling of missing required parameters, but this is partially implied by the schema. The description is sufficiently complete for a read tool with strong annotations.

    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?

    The schema already describes the 'source' and 'sources' parameters with coverage of 50%. The description adds the nuance that search must be 'unambiguous', which is useful, but it does not explain timeout_ms or max_output_bytes. Overall, the description provides minimal additional parameter semantics.

    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 tool's function with a specific verb ('Resolve and fetch') and resource ('Notion pages'), and includes the scope of up to eight pages. It also distinguishes itself from the sibling 'notion_publish_document' by focusing on reading, not writing.

    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 clear context: it is for reading/fetching Notion documents, which is distinct from the sibling publish tool. It does not explicitly mention when to use alternatives, but the tool name and description make the intended use obvious.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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