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tzero-mcp

by toprakahmetaydogmus
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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

    A4.3/5.0

    Scored across 21 tools

    Disambiguation4/5

    Tools target distinct code-analysis operations (context generation, dependency graphs, architecture rules, quality audits, token metrics). Sibling Routing guidelines explicitly differentiate overlapping tools like get_project_context_tree vs get_smart_skeleton_context and analyze_change_impact vs trace_symbol_call_chain. However, several graph-analysis tools (query_module_dependencies, analyze_change_impact, trace_symbol_call_chain, rank_repository_pagerank) have adjacent scopes that could still cause occasional misselection.

    Naming Consistency5/5

    All tool names are snake_case and follow a verb_noun structure (get_*, query_*, generate_*, audit_*, etc.). The specific verbs vary but are semantically appropriate and consistent, with no camelCase or chaotic style.

    Tool Count3/5

    21 tools is in the heavy range (16-25) for a single server. Although each appears to serve a distinct sub-purpose, the set is large enough that discovery and selection may be cumbersome.

    Completeness4/5

    The surface covers major static-analysis workflows: context generation, dependency mapping, impact analysis, call tracing, architecture enforcement, security scanning, quality audits, and token metrics. Some gaps exist, such as no direct symbol-by-name lookup beyond semantic search or no runtime/test coverage analysis, but these are minor for the apparent read-only static-analysis domain.

    Maintenance

    ActivityMaintained
    ResponsivenessWithin a week

    Resources