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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

update_notebook

Modify an existing Datadog notebook by its ID to update monitoring dashboards, log views, or metric visualizations for improved observability.

Instructions

Update a notebook using the specified ID.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "update_notebook"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden. It fails to disclose any behavioral traits: it doesn't specify if this is a mutation (implied but not stated), what permissions are required, whether changes are reversible, rate limits, or what the response looks like. For a tool with zero annotation coverage, this is a critical gap.

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, efficient sentence with no wasted words. It's front-loaded with the core action ('Update a notebook'), making it easy to parse quickly. Every part of the sentence contributes directly to the tool's purpose.

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?

Given the complexity (an update operation), lack of annotations, no output schema, and 0 parameters, the description is incomplete. It doesn't explain what 'update' entails, what data is returned, or any side effects. For a mutation tool with no structured support, this leaves the agent under-informed about critical behavioral aspects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% description coverage, so no parameters need documentation. The description mentions 'using the specified ID', which implies an ID parameter, but since the schema shows no parameters, this is contradictory or misleading. However, with 0 parameters, the baseline is high as there's little to explain, though the mention of an unspecified ID is confusing.

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

Purpose3/5

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

The description states the verb ('Update') and resource ('a notebook'), which provides a basic purpose. However, it's vague about what aspects can be updated (e.g., content, metadata, settings) and doesn't distinguish from sibling tools like 'notebooks_update' or 'update_synthetics_test_v1'. It merely restates the tool name with minimal elaboration.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a notebook ID), context (e.g., after creation), or exclusions (e.g., not for deleting). With many sibling tools (e.g., 'notebooks_update', 'update_dashboard'), the lack of differentiation leaves the agent guessing.

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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