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Agent Context Optimizer MCP

by AiAgentKarl
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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

    A3.5/5.0

    Scored across 5 tools

    Disambiguation4/5

    Tools are mostly distinct: analyze_task recommends server combinations with token estimation, while estimate_context_usage specifically estimates context usage for a given set. optimize_server_set and suggest_minimal_set both aim to reduce server count but differ in starting point (existing vs. from scratch). There is slight overlap but descriptions clarify purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., analyze_task, get_server_catalog). The naming is predictable and uniform, making it easy for an agent to understand the action and target.

    Tool Count5/5

    With 5 tools, the server is well-scoped for its purpose of optimizing MCP server context. The number feels neither too sparse nor excessive, covering key functionalities without unnecessary bloat.

    Completeness4/5

    The tool surface covers the core workflow: analyzing tasks, estimating context, getting catalog, and optimizing server sets. A minor gap is the lack of a tool to directly apply or save the optimization, but as an advisor, it is sufficiently complete.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources