"AURA API documentation and integration guide" matching MCP servers:

Enables AI assistants to securely access local machine capabilities such as file operations, shell commands, Skills, and Pi Tools through a controlled MCP interface with token authorization and multiple tunnel options.

Enables AI tools to understand a database, inspect schema, and run safe SELECT queries with SQL guardrails, plus optional codebase reading.

Integration project for Model Context Protocol (MCP) servers with Claude Desktop App, enabling filesystem operations, development support, and file management through natural language.

A comprehensive MCP server with RESTful API that enables file operations, command execution, project management, and AI integration for remote development control with security features and real-time communication.

Provides a complete end-to-end MCP server implementation with file system tools, web scraping capabilities, and system information access. Includes ready-to-use configuration files and integration examples for Claude Desktop, ChatGPT, and other AI models.

MCP server for the Stashcat messenger API. Enables AI assistants to read and send messages, manage channels, conversations, files, polls, and more.

MCP server that provides file operations and Moonshot API-powered tools (reasoning, code review, testing, research, web search, agent) for Kimi K2.5, requiring only a Moonshot API key.

Enables AI clients to read, write, search, and manage files in an Obsidian vault via MCP over SSE, running standalone without the Obsidian desktop app.

Enables conversion between PDF/Office documents and structured JSON, supporting extraction and generation of document content.

Enables AI assistants to interact with PDF documentation files stored locally. Provides tools to list, read, search, and extract metadata from CRM API documentation PDFs through natural language queries.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

A bridge server that allows LLM tools to interact with an Obsidian vault through a local REST API, enabling file operations, note management, and metadata access through natural language.

A server implementation that enables LLMs to programmatically manage tasks in Todo.txt files using the Model Context Protocol (MCP), supporting operations like adding, completing, deleting, listing, searching, and filtering tasks.

Enables AI assistants to inspect Ignition gateway backups, project exports and tag exports locally and turn them into an editable engineering reference and manual pack workspace. Runs over stdio so agents can explain, validate and complete the evidence-traced documents without uploading anything.

Enables AI agents to read, create, update and delete any file in a mounted folder of markdown notes, patch individual headings, blocks or frontmatter keys, search by text or JsonLogic queries over frontmatter, tags and links, and stream note changes as events. Runs as a standalone container requiring no Obsidian installation and binds only to private networks such as Tailscale or WireGuard.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables agents to read, search, batch process, and watch directories of resume files via JSON-RPC MCP methods and resource discovery.

Enables MCP clients to interact with a filesystem by listing, reading, writing, and monitoring files, as well as extracting resume text and batch processing files.

Enables file system operations (read, write, list, search, watch, batch process) via MCP over JSON-RPC 2.0, used by a resume matching agent.

Provides file system access for resume matching through JSON-RPC, enabling semantic search and workflow orchestration with LangGraph.