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perejaslav

DirectAI MCP

by perejaslav
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Python
Local

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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

    B3.1/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool maps to a distinct stage or resource: account listing, catalog search, action introspection, read execution, write planning, write application, and logging. The plan/apply pair is complementary rather than ambiguous, and read/execute vs. catalog search are clearly separated.

    Naming Consistency5/5

    All tool names follow a consistent lowercase snake_case verb-first pattern: list_, search_, describe_, run_, plan_, apply_, get_. The naming style is uniform and predictable across the entire set.

    Tool Count5/5

    Seven tools is well within the ideal range and each tool earns its place in the workflow. The count matches the server's apparent scope: account discovery, action inspection, read execution, and a two-phase write flow.

    Completeness4/5

    The toolset covers the main lifecycle well: discover accounts, search and describe actions, run reads, plan writes, apply them, and review the operation log. Minor gaps exist, such as no explicit cancel-plan operation or fetching a single log entry by ID, but agents can work around these.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources