"Importing FastMCP from the mcp.server Python Module" matching MCP servers:

Enables creation and management of Terraform modules for Facets.cloud infrastructure with interactive generation, validation, forking, testing, and deployment workflows through secure file operations and FTF CLI integration.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Enables developers to build production-grade MCP services with dependency injection, zero global state, layered imports, and a sample user-notes tool, resource, and prompt. It includes Testcontainers, Prometheus metrics, Kubernetes probes, and structured logging for testable local and production deployments.

A simple MCP server for task management with Bearer token authentication, supporting create, complete, and list tasks operations.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Provides SQL database access via MCP, supporting PostgreSQL, MySQL, and SQLite with tools for listing tables, getting schemas, and executing queries.

Enables interaction with openGauss databases through multiple transport methods (Stdio, SSE, Streamable-Http). Supports database operations and queries with configurable connection parameters.

A secure and efficient MCP server for MySQL database operations, enabling LLMs to execute SQL queries with read-only access by default and optional write permissions.

Enables deploying production-ready MCP servers with built-in authentication, rate limiting, data desensitization, audit logging, and session isolation, ready for Kubernetes.

Provides a central gateway to 170+ offline mock MCP servers with deterministic fixture-based responses and per-server SQLite state, enabling realistic credential-free agent trajectory testing and multi-step workflow rehearsal.

A boilerplate MCP server built with Python and FastMCP, ready for deployment on Render, with example tools and logging.

A temporally-aware knowledge graph MCP server for AI agents, enabling episodic ingestion, entity management, and semantic search with support for multiple LLM and embedding providers.

Enables AI agents to access approved public and private website endpoints through governed MCP tools, with operator-reviewed registries, scoped authentication, and bounded responses.

A custom implementation for real-time supply chain optimization that enables parallel tool calling to provide intelligent inventory management recommendations and actionable insights in response to live supply chain events.

A Python-based MCP server demonstrating basic math and text tools, supporting both SSE and STDIO transports for integration with AI assistants like Cline in VS Code.

MCP server for controlling satellite ground station operations in the Trench simulation, including pass management, downlink control, and antenna pointing.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A Model Context Protocol server that brings the capabilities of enigmapython library to LLMs, allowing them to encrypt and decrypt messages using historically accurate Enigma machine emulators

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.