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Related Servers

Alternatives to cc-sensei

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables Claude Code and AI coding agents to retrieve compact, task-shaped code evidence bundles via MCP, combining AST-aware retrieval, hybrid BM25+FAISS search, call-graph traversal, reranking, and token-budgeted context assembly.
      1
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      An MCP server that gives Claude structural understanding of a codebase—dependency graph, entry points, complexity ranking, and import cycles—without reading every file into context.
      4
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    • A
      license
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      quality
      D
      maintenance
      Persistent codebase knowledge layer for AI agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) and serves via MCP. 28 languages, 14 tools, ~85% token reduction.
      11 npm
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    • A
      license
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      quality
      B
      maintenance
      Enables AI coding agents to index codebases into a queryable knowledge model and ask for the smallest architectural surface a task likely touches, with evidence, confidence, and freshness, via MCP tools.
      216 PyPI
      Apache 2.0
    • A
      license
      A
      quality
      C
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      Extract domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x — gathers and makes concepts, naming conventions, and vocabulary queryable via MCP.
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    TDQS

    A4.2/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: listing modules, getting module content, searching architecture knowledge, searching patterns, tracing concerns, and reading source code. No two tools overlap significantly, and descriptions clarify any potential ambiguity.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (e.g., get_module, list_modules, trace_concern) with clear, descriptive verbs. No mixing of conventions.

    Tool Count5/5

    Six tools is well-scoped for an architectural knowledge base, providing essential operations without being overwhelming. Each tool serves a necessary role.

    Completeness5/5

    The tool surface covers all major activities: discovering modules (list_modules), retrieving module details (get_module, get_source_code), searching across the knowledge base (query_architecture, trace_concern), and accessing design patterns (search_patterns). No obvious gaps for a read-only reference server.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues