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journal-scout-mcp

by mahdyarief
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Python
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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

    C2.5/5.0

    Scored across 17 tools

    Disambiguation3/5

    Some tools have overlapping purposes: get_author_profile and scival_author_lookup both retrieve author information but from different systems, and get_paper vs get_abstract_details both resolve paper metadata. The individual search_* tools are clearly distinct by source, but the SciVal metrics vs lookup tools may confuse an agent. Overall, boundaries are mostly clear but not every tool has a sharply distinct role.

    Naming Consistency3/5

    The search_* and get_* tools follow a consistent verb_noun pattern, but the scival_* tools break this by using a noun_prefix with no verb (e.g., scival_author_metrics vs. get_scival_author_metrics). Within the scival group naming is consistent, but mixing two conventions across the server reduces predictability. The pattern is readable but not uniform.

    Tool Count4/5

    At 17 tools, the count is slightly above the typical 3-15 sweet spot but still well-scoped for a multi-source scholarly search and metrics server. The number feels justified given the many supported APIs (Scopus, arXiv, OpenAlex, etc.) and SciVal's separate lookups/metrics. It is not excessive and each tool appears to serve a plausible need.

    Completeness4/5

    The surface covers the core academic search workflow: combined and source-specific searches, paper resolution, citation graph, author profiles, and SciVal metrics. Minor gaps exist, such as no direct full-text retrieval (only open-access links) and no journal-level search or repository export functionality, but these are not critical for the apparent purpose. Agents can accomplish typical research tasks without dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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