"Créer des systèmes de prompt pour les modèles de langage (LLM)" matching MCP servers:

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

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

An MCP server for a plain-markdown LLM wiki vault with YAML frontmatter and Obsidian-style wiki-links, enabling headless full-text search, note reading, backlink discovery, and safe append/create-only writing with path traversal protection and an immutable raw/ directory.

Enables parsing German bank statement PDFs into structured, validated transaction data, exporting all transactions as German-style CSV, and verifying statement totals via proof calculations, all locally within MCP-compatible clients.

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

Graph-level operations for Karpathy LLM Wiki knowledge bases, enabling LLM agents via MCP and humans via CLI to perform structured graph surgery including node/edge CRUD, wikilink management, index rebuilding, and graph metrics.

A KISS self-hosted wiki server for AI agents, providing MCP tools to list, read, search, write, and append notes to Markdown files on the filesystem.

Enables building and querying a local wiki knowledge base from raw source files via MCP tools and a PyQt viewer.

MCP server to interact with Cleyrop work data: browse, search, read file content, and manage files/folders.

Enables orchestrating models to delegate reading and answering questions about local files to a local LLM, avoiding sending file contents through the orchestrator's context.

MCP server that enforces single-use human confirmations for sensitive tool calls, sanitizes prompts against prompt injection, and re-validates file paths before destructive actions.

A local MCP server that runs Llama models entirely on your machine. No API keys, no cloud costs, 100% private and offline-capable.

Enables LLM agents to safely reclaim disk space by deleting build artifact directories like node_modules, .venv, and target, with strong guardrails to prevent accidental or malicious deletion.

A lightweight, file-based server for managing and serving personal prompt templates with variable substitution support via the Model Context Protocol. It allows users to store, update, and organize prompts in a local directory through integrated MCP tools and CLI assistants.

Enables natural language file operations and intelligent file analysis via MCP, supporting CRUD actions and multi-step reasoning for directory management.

Servidor MCP para busca e normalização de citações de leis brasileiras em arquivos de texto locais.

A security-first MCP server that provides LLMs with structured tools for filesystem, process, search, build/test/lint, IDE integration, and more.

Enables loading and serving markdown files as prompts from local folders or GitHub repositories. Supports automatic repository synchronization and YAML frontmatter for prompt metadata.

MCP server for exporting PDF to markdown, optimized for LLM consumption.

A demonstration MCP server showcasing tools (calculator, file operations, weather, timestamp), resources (server config, system info, documentation), and reusable prompt templates for code review, documentation, and debugging.