8 Best ToolHive Alternatives in 2026 (Open Source)
ToolHive — ToolHive is an enterprise-grade platform for running and managing Model Context Protocol (MCP) servers.. Only dedicated MCP server management platform with enterprise-grade security (container isolation, SSO, registry governance) — vs manually configuring MCP servers or using generic container tools
These 8 open-source tools do the same job. They are ordered by how closely they match ToolHive, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| ToolHive(original) | 2.2k | +88 | 2026-09-30 |
| Casibase | 5.7k | +191 | 2026-09-29 |
| Arcade MCP | 1.0k | +34 | 2026-09-29 |
| Eidolon | 492 | +1 | 2024-12-19 |
| Agno | 42.4k | +551 | 2026-09-30 |
| Langflow | 155.4k | +1,457 | 2026-09-29 |
| LangStream | 427 | +1 | 2024-05-20 |
| BentoML | 8.9k | +52 | 2026-09-07 |
| AI Gateway | 13.1k | +328 | 2026-05-25 |
1. Casibase
⚡️AI Cloud OS: Open-source enterprise-level AI knowledge base and MCP (model-context-protocol)/A2A (agent-to-agent) management platform with admin UI, user management and Single-Sign-On⚡️, supports Ch
What sets it apart: vs other knowledge base platforms: Enterprise-grade open-source AI Cloud OS with built-in SSO (Casdoor), admin UI, MCP/A2A agent management, and support for 10+ LLM providers out of the box
Best for: Enterprise teams needing a self-hosted AI knowledge base with admin UI; Organizations requiring SSO and user management for AI chatbots; Multi-model AI platform deployment with MCP/A2A support
2. Arcade MCP
The best way to create, deploy, and share MCP Servers
What sets it apart: vs raw MCP SDK: built-in OAuth2 auth, secret injection invisible to LLMs, and one-command project scaffolding with CLI
Best for: Building secure MCP tool servers for AI assistants; Teams needing OAuth-based tool calling with secret management
3. Eidolon
The first AI Agent Server, Eidolon is a pluggable Agent SDK and enterprise ready, deployment server for Agentic applications
What sets it apart: vs LangChain/CrewAI: agents are deployed as HTTP services with built-in server, enabling true microservice agent architectures with dynamic inter-agent tool discovery
Best for: Deploying agents as production HTTP services; Multi-agent systems needing inter-agent communication
4. Agno
Build, run, manage agentic software at scale.
What sets it apart: Production-first agent runtime with built-in session isolation, approval workflows, and scalable FastAPI serving — unlike LangChain which is framework-first
Best for: Production multi-agent systems with session isolation; Enterprise agentic applications needing approval workflows and audit trails
5. Langflow
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
What sets it apart: Best visual builder for LLM workflows with direct MCP server deployment — more production-ready than Flowise with API-first architecture
Best for: Rapid prototyping of AI agent workflows with visual builder; Non-developers building LLM applications without coding
6. LangStream
LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka.
What sets it apart: vs LangChain / LlamaIndex: event-driven Kubernetes-native AI platform with first-class Kafka/Pulsar integration — designed for enterprise data pipeline architectures, not notebook-to-production workflows
Best for: Enterprise teams building event-driven AI data pipelines at scale; Organizations with existing Kafka/Pulsar infrastructure wanting LLM integration; Kubernetes-native AI application deployment with production-grade messaging
7. BentoML
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
What sets it apart: Unified model serving framework with Bento packaging — turn any model into a production API with automatic Docker, adaptive batching, and multi-model orchestration
Best for: Teams deploying ML/AI models as production APIs; Applications needing dynamic batching and GPU optimization; Multi-model inference pipelines (LLM + embedding + reranker)
8. AI Gateway
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
What sets it apart: vs LiteLLM: production-focused with guardrails, caching, and MCP Gateway; vs OpenRouter: self-hostable with enterprise governance and conditional routing rather than just model access
Best for: Teams using multiple LLM providers needing unified routing; Production AI apps requiring reliability (retries/fallbacks); Organizations wanting centralized LLM cost and access control