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"Parsing and Unparsing CSV Files for AI Context Use" matching MCP servers:

  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides AI coding agents with ground truth about a Rails app via 45 read-only tools covering schema, models, routes, controllers, views, jobs, and conventions, working over MCP or CLI and functioning even when the app cannot boot.
    153
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    An MCP server that edits files through a real Neovim instance, giving agents access to LSP diagnostics, formatting, code actions, and plugin commands.
    18
    17
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.
    250
    25
    Apache 2.0
  • A
    license
    Not graded
    quality
    C
    maintenance
    Provides real structural understanding of a codebase via tree-sitter AST parsing before starting a task, reducing token waste and grounding acceptance criteria in code structure.
    MIT
  • F
    license
    Not graded
    quality
    A
    maintenance
    MCP server that validates AI-generated 1C:Enterprise (BSL) code against the real platform API. Catches unknown enum values, wrong argument counts, and missing type members by parsing the platform syntax-helper (shcntx_ru.hbk) — independent Rust implementation with built-in expression validator.
    19
  • A
    license
    A
    quality
    B
    maintenance
    MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.
    3
    29
    8
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.
    8
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.
    11
    433
    58
    Elastic 2.0
  • A
    license
    A
    quality
    D
    maintenance
    Enables efficient code navigation and retrieval through natural language search, BM25 ranking, and fuzzy matching across multiple programming languages. It drastically reduces token usage by allowing Claude to query specific code symbols and logic instead of reading entire files.
    13
    33
    13
    MIT
  • F
    license
    A
    quality
    C
    maintenance
    A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.
    3
  • A
    license
    A
    quality
    A
    maintenance
    Provides persistent memory and a codebase knowledge graph for AI coding assistants, enabling shared context across multiple tools like Claude, Cursor, and ChatGPT, with significant token reduction.
    5
    32
    MIT
  • A
    license
    A
    quality
    Not graded
    maintenance
    Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.
    3
    11
  • A
    license
    B
    quality
    A
    maintenance
    Enables LLMs to efficiently read, write, and refactor code using precise AST-based operations, reducing token usage and context window waste.
    25
    57
    3
    MIT
  • F
    license
    C
    quality
    D
    maintenance
    A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.
    3
    26
    1