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Amazon Managed Prometheus MCP Server

by sigitp-git
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Python
Remote

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    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

    A3.5/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: list_workspaces enumerates all workspaces, get_workspace retrieves detailed information, get_workspace_status checks status, and query_metrics executes PromQL queries. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: list_workspaces, get_workspace, get_workspace_status, and query_metrics. The naming is predictable and readable throughout.

    Tool Count4/5

    Four tools is reasonable for a focused Prometheus monitoring server, covering core operations like listing, retrieving, checking status, and querying. It might be slightly thin for full CRUD operations, but it aligns well with the server's purpose.

    Completeness3/5

    The tools cover read and query operations effectively, but there are notable gaps in write operations (e.g., create, update, or delete workspaces). This limits agents to monitoring and querying without management capabilities, which could be a constraint for full lifecycle workflows.

    Resources