Alternatives to gotoolkits/DifyWorkflow

🏎️ 🏠 - Kubernetes bulk port forwarding with service discovery, /etc/hosts management, traffic monitoring, and pod log streaming

Beelzebub is an open-source deception framework (a honeypot framework) for deploying decoy services and capturing attacker interactions as security evidence. Services, routes, and response rules are defined in YAML with static handlers or LLM-powered responses across SSH, HTTP, TCP, TELNET, and MCP protocols; events can be inspected in local logs, published to RabbitMQ, or reported to Beelzebub Platform, with Prometheus metrics for monitoring.

🏎️ 🏠 A - powerful Kubernetes MCP server with additional support for OpenShift. Besides providing CRUD operations for **any** Kubernetes resource, this server provides specialized tools to interact w

🏎️ 🏠 - MCP Language Server helps MCP enabled clients navigate codebases more easily by giving them access to semantic tools like get definition, references, rename, and diagnostics.

🏎️ ☁️/🏠 - Provides MCP multi-cluster Kubernetes management and operations, featuring a management interface, logging, and nearly 50 built-in tools covering common DevOps and development scenarios. S

🏎️ ☁️/🏠 - Kubernetes cluster operations through MCP

Foxy Contexts is a Go library for building MCP servers declaratively: developers define tools, resources, and prompts and register them with an app builder that uses uber/fx dependency injection under the hood. It implements the server side of the protocol with stdio, SSE, and streamable HTTP transports, and ships a foxytest package for functional testing.

🏎️ 🏠 - A MCP server for interacting with and benefit from advanced Go code analysis features.

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster

A curated, community-maintained list of Model Context Protocol (MCP) servers, organized by category, with sections for MCP clients, tutorials, and community resources. The repository is a directory of production-ready and experimental servers that extend AI capabilities through file access, database connections, and API integrations; it is a list, not a runnable MCP server itself.

🐍 - A high-level framework for building MCP servers in Python

MCP server that connects Blender to LLM clients through a Blender addon and a socket-based connection. It lets an AI create, modify, and delete 3D objects, apply materials and colors, execute Blender Python code, and pull in assets from Poly Haven, Sketchfab, and Poly Pizza, with multi-angle views and renders so the model can check its own work.