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Jules AI MCP Server

by Helfstein-one
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    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

    A3.6/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool maps to a distinct action in the Jules task lifecycle: list, create, status, approve, feedback, diff, cancel. The read-style tools (get_task_status vs get_diff) are clearly distinguished by what they return, and approve_plan vs send_feedback are separated by their distinct purposes. No two tools can be reasonably confused.

    Naming Consistency5/5

    All names follow a strict 'jules_verb_noun' snake_case pattern, e.g. jules_list_tasks, jules_create_task, jules_cancel_task. The prefix is applied uniformly and verbs are unambiguous. There is no deviation in style.

    Tool Count5/5

    Seven tools is well-scoped for managing an autonomous coding-task lifecycle. Each tool earns its place with no redundancy or filler. This sits comfortably in the ideal range.

    Completeness4/5

    The set covers the full workflow: create, list, observe status, gate the plan via approval, steer mid-session, retrieve diffs/PR, and abort. Minor gaps remain, e.g. no explicit way to fetch or merge the final PR artifact once complete, but agents can work around this via get_diff.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources