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sbarron

Ambiance MCP Server

by sbarron

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    • A
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      C
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      Provides AI-powered code intelligence for any codebase using local LLMs and vector search, enabling semantic code search, pattern analysis, and context-optimized code generation with 90% token savings.
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    • A
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      Provides structured, token-efficient code context for AI assistants by indexing codebases with AST-level analysis, supporting 17+ languages, enabling semantic search, call-site tracking, and PR attribution.
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    • A
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      Make any LLM a codebase expert instantly. Provides deep code intelligence through semantic search, architecture mapping, security analysis, and smart context that fits perfectly in token windows.
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    TDQS

    A3.8/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: ast_grep_search is for structural code search, frontend_insights analyzes web architecture, local_context provides general query-aware retrieval, local_debug_context focuses on debugging, local_file_summary gives file-level analysis, and local_project_hints offers project navigation. The descriptions reinforce these unique roles, making tool selection unambiguous.

    Naming Consistency4/5

    The naming is mostly consistent with a clear pattern: all tools use snake_case and start with a descriptive prefix (ast_grep_, frontend_, local_) followed by a noun or noun phrase. The minor deviation is that 'frontend_insights' uses a compound noun while others are simpler (e.g., 'local_context'), but this doesn't hinder readability or predictability.

    Tool Count5/5

    With 6 tools, the count is well-scoped for a code analysis and development assistance server. Each tool serves a specific, valuable function (e.g., search, insights, context, debugging, file summary, project hints), and none feel redundant or out of place, fitting a typical range for such a domain.

    Completeness5/5

    The tool set provides comprehensive coverage for code analysis and development workflows: it includes search (ast_grep_search), architectural analysis (frontend_insights), context retrieval (local_context), debugging (local_debug_context), file-level inspection (local_file_summary), and project navigation (local_project_hints). There are no obvious gaps; agents can handle tasks from low-level code examination to high-level project understanding.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues