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achatainga

mcp-code-context

by achatainga

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      Enables precise source code retrieval via tree-sitter AST parsing, cutting AI token costs by 86-99% by indexing codebases and fetching only needed symbols and structural queries (e.g., blast radius, importers) on demand.
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    • A
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      MCP file cache for AI coding agents. Re-reading an unchanged file costs ~40 tokens instead of the whole file; a changed file comes back as a diff. Adds grep, BM25 search and glob over cached files, atomic edits with dry_run, and token-budgeted batch reads. One local daemon serves every client. No API keys, no GPU. Works with Claude Code, Cursor, VS Code, Codex and OpenCode.
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    • A
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      Provides intelligent code context and analysis through semantic compression, AST parsing, and multi-language support. Offers 60-80% token reduction while enabling AI assistants to understand codebases through local analysis, OpenAI-enhanced insights, and GitHub repository integration.
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    TDQS

    B3.4/5.0

    Scored across 25 tools

    Disambiguation4/5

    Most tools have distinct purposes, but some overlap exists (e.g., read_file_surgical and explain_symbol both retrieve symbol information, though with different focuses). Descriptions generally clarify boundaries.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern. Verbs like get_, read_, search_, and direct verbs (clean, clear, insert) are used uniformly per function.

    Tool Count3/5

    With 25 tools, the server is at the high end of the 'heavy' range. While the number is justified by the breadth of features (reading, writing, analysis, state management), it feels slightly bloated for a typical code context server.

    Completeness4/5

    The tool surface covers core read, write, search, and analysis operations well. However, there is no explicit create/delete file tool, and file-level operations are limited, leaving minor gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues