"Prompt Enhancer MCP Search" matching MCP servers:

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

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.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

A production-style MCP server that lets Claude Desktop search your local documents using TF-IDF keyword search. No heavy frameworks, just plain Python and the official MCP SDK.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

A Model Context Protocol server that enables keyword search within files, returning matching lines with line numbers.

Integrates Everything Search with Claude Code for lightning-fast file searching across entire drives, up to 400x faster than traditional methods.

Enables AI models like Claude to manage local prompt files with CRUD operations, fuzzy search, categorization, templates, version control, and favorites.

Integrates Everything file search with Claude Desktop, enabling instant Windows filesystem search via natural language queries.

High-performance MCP server giving AI agents advanced filesystem and automation capabilities on Windows, with 26 tools across file I/O, search, Git, process management, and more.

Provides integration with Everything Search Engine allowing powerful file search capabilities through the Model Context Protocol with advanced search options like regex, case sensitivity, and sorting.

Provides custom prompts for Amazon Q by serving markdown files from the local filesystem as prompt templates through the Model Context Protocol.

Enables AI models to search, read, and analyze Excel files from your local file system with support for multiple worksheets, text search, and JSON data conversion.

A high-performance Model Context Protocol (MCP) server built for Windows. Leveraging the native Everything SDK, it provides AI models (like Claude, GPT, Gemini) with millisecond-speed file searching, statistical analysis, and disk usage insights.

Enables searching for a keyword within a text file using Model Context Protocol tools via standard input/output.

Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.

A modular framework for building and running multiple MCP servers with file operations, system information, and extensible tool/prompt/resource support.

A plug-and-play MCP server that adds zero-boilerplate tools like file search, reliability scoring, and prompt injection detection to any MCP-compatible agent.

Integrates with Everything Search Engine to provide lightning-fast file search capabilities across Windows systems using natural language queries and advanced filtering options through MCP-compatible applications.