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Ollama MCP Server

by NightTrek
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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

    B3/5.0

    Scored across 10 tools

    Disambiguation4/5

    Most tools have distinct purposes, such as list, pull, push, rm, and show, which clearly target different operations on models. However, 'run' and 'chat_completion' could be confused, as both involve executing models, though 'chat_completion' is more specific to API interactions. Overall, the descriptions help clarify boundaries, but there is some overlap in execution-related tools.

    Naming Consistency3/5

    The naming is mixed with some inconsistencies: most tools use simple verb forms like list, pull, push, rm, run, and serve, which are consistent. However, 'chat_completion' uses snake_case and is more descriptive, while 'cp' and 'create' are shorter forms that deviate slightly. This creates a readable but not fully uniform pattern across all tools.

    Tool Count5/5

    With 10 tools, the count is well-scoped for managing Ollama models, covering essential operations like listing, creating, pulling, pushing, removing, running, and serving. Each tool serves a clear purpose in the model lifecycle, making the set comprehensive without being overwhelming or too sparse for the domain.

    Completeness5/5

    The tool set provides complete coverage for Ollama model management, including CRUD operations (create, list, rm), lifecycle actions (pull, push, run, serve), and informational tools (show, chat_completion). There are no obvious gaps; agents can perform all core workflows from model acquisition to execution and maintenance seamlessly.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

    Resources