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Project Brain

by Perlitten
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Python
Hybrid

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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

    C2.8/5.0

    Scored across 13 tools

    Disambiguation3/5

    record_task_observation and record_task_lesson both capture L1 task evidence, differing mainly in strength; prepare_task_context and prepare_deep_context both prepare context, and impact_analysis/find_related_files overlap in graph analysis. Descriptions help, but an agent must read carefully to choose correctly.

    Naming Consistency4/5

    Most names follow a verb_noun snake_case pattern (record_task_observation, prepare_task_context, get_background_job, search_code, find_related_files, review_diff). impact_analysis is a noun phrase without a verb, a minor deviation from the otherwise consistent convention.

    Tool Count5/5

    13 tools is well within the ideal 3-15 range for a project memory and code intelligence server. Each tool appears to serve a distinct purpose, and the set is neither bloated nor thin.

    Completeness3/5

    The server offers many recording tools (observation, lesson, outcome, decision, rule) and analysis/retrieval helpers (ask_project, prepare_context, search_code, find_related_files, impact_analysis). However, there is no direct way to retrieve, list, update, or approve recorded memory, and the mentioned L3 human approval step is not exposed as a tool, leaving notable lifecycle gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources