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datadog-mcp

by techskies11
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Python
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    • Datadog MCP Server

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.1/5.0

    Scored across 30 tools

    Disambiguation5/5

    Each tool targets a distinct resource and action, with clear boundaries between overlapping domains like logs, metrics, and APM. Tools such as search_logs, count_logs, and aggregate_logs_by_field are explicitly differentiated to prevent misuse, and descriptions cross-reference each other to guide correct selection.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using lowercase with underscores, such as get_*, list_*, search_*, count_*, create_*, update_*, and silence_*. No mixed conventions or camelCase appear, making the naming predictable and easy to navigate.

    Tool Count2/5

    With 30 tools, the server exceeds the 25-tool threshold for 'too many' and is well above the typical 3-15 tool range. While each tool serves a distinct purpose across multiple Datadog domains, the sheer number adds cognitive load for an agent and may require extra effort to choose correctly.

    Completeness3/5

    The toolset covers core workflows for logs, metrics, APM, dashboards, monitors, and downtimes, including create, read, and update operations. However, there are no delete operations for any resource (e.g., monitors, dashboards, downtimes), which is a notable gap in lifecycle management. Some areas, like APM services, only provide list functionality without deeper detail.

    Maintenance

    ActivityStale
    ResponsivenessNo issues

    Resources