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CogniRepo

by ashlesh-t
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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

    B3.4/5.0

    Scored across 35 tools

    Disambiguation3/5

    Several tools serve overlapping search/retrieval purposes: semantic_search_code vs search_token vs lookup_symbol vs subgraph all handle code discovery, and cross_repo_search vs org_wide_search vs org_search heavily overlap (though descriptions try to establish a hierarchy). The descriptions help differentiate primary vs fallback, but an agent could still confuse episodic_search vs retrieve_memory vs store_memory, and get_session_brief vs get_agent_bootstrap vs get_last_context all serve session-start context.

    Naming Consistency3/5

    Naming is mostly verb_noun (retrieve_memory, record_decision, search_docs, explain_change, link_repos), but there are notable inconsistencies: org_search vs org_wide_search vs cross_repo_search have parallel but semantically overlapping structures, and get_session_brief/get_last_context/get_agent_bootstrap/get_session_history all use get_* while also mixing nouns without a clear pattern. Some names are vague (subgraph, context_pack, who_calls) while others are very specific.

    Tool Count2/5

    35 tools is excessive for a code-knowledge memory server. Many tools overlap or are variants of each other (e.g., three cross-repo search tools, four session-bootstrap tools, multiple memory retrieval tools). A well-scoped server would likely need 15-20 tools; 35 creates navigation burden and redundancy.

    Completeness4/5

    The server covers the domain of knowledge capture, retrieval, graph relationships, and session context fairly comprehensively: memory stores, episodic logs, symbol lookup, dependency traversal, service endpoints, error tracking, and user preferences. Minor gaps exist (no obvious tool for deleting memories or removing repos, no direct tool for listing all memories), but agents can work around these via supersede_learning and the existing search tools.

    Maintenance

    ActivityActive
    ResponsivenessUnresponsive

    Resources