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Obrais-cloud

ollama-fleet-mcp

by Obrais-cloud
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Python
Local

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    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    A4/5.0

    Scored across 6 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: list_models for inventory, fleet_health for status, pull_model for downloading, compare_models for side-by-side comparison. However, generate and smart_generate both perform text generation and differ only in routing logic (explicit host vs auto-route), which could cause misselection.

    Naming Consistency3/5

    Naming conventions are mixed: list_models and pull_model use verb_noun, generate is a bare verb, fleet_health is a noun phrase, smart_generate is adjective_verb. The names are readable but do not follow a single consistent pattern.

    Tool Count5/5

    Six tools is a well-scoped set for an Ollama fleet management server, covering the essential operations of listing models, generating responses, checking health, comparing models, and pulling models without unnecessary bloat.

    Completeness4/5

    The tool surface covers the core workflows: inventory (list_models), generation (generate, smart_generate), comparison (compare_models), health monitoring (fleet_health), and model acquisition (pull_model). Missing operations like delete_model or model detail inspection are minor gaps that agents can work around.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources