agentgateway
★ 5.7k
vs
archestra
★ 4.4k
agentgateway vs archestra
agentgateway: Agentgateway is an open-source proxy offering a complete connectivity solution for Agentic AI, built on AI-native protocols like MCP and A2A. It provides security, observability, and governance for agent-to-LLM, agent-to-tool, and agent-to-agent communication across various frameworks.; archestra: Archestra is a secure, MCP-native AI platform that simplifies enterprise AI adoption. It provides comprehensive tools for AI orchestration, security against prompt injections and data exfiltration, cost management, and observability across the organization.
01
TL;DR
agentgatewayObservability · ★ 5.7k
When to choose:
- You want one proxy for LLM calls (OpenAI-compatible API with spend controls, failover and load balancing), MCP tools and A2A traffic.
- You need guardrails from several sources: regex, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor or webhooks.
- You need security and observability built in: JWT, API keys, OAuth, RBAC with a CEL policy engine, rate limiting, TLS and OpenTelemetry.
When to skip:
- You only need to bridge one MCP transport: a small proxy is simpler.
- You want the inference-routing features without Kubernetes: the README ties them to Kubernetes Inference Gateway extensions.
- You want detailed setup instructions in the README: it is short and points to the documentation site.
archestraObservability · ★ 4.4k
When to choose:
- You are a platform or security team that needs central control over how the company uses models and MCP servers.
- You want one platform covering an internal chat, an LLM gateway, an MCP gateway and registry, and an agent runtime.
- You need SSO, RBAC, sandboxed code execution, guardrails, per-user tool authorisation, OpenTelemetry and Prometheus.
When to skip:
- You are a small team that only needs a proxy: Kubernetes-oriented components make this a significant deployment.
- You need to avoid AGPL or commercial terms: the default code is AGPL-3.0 and parts marked Enterprise are under a commercial licence.
- You already run gateways or chat apps whose roles overlap; plan what it would replace.
02
Side-by-Side Comparison
Field
agentgatewayarchestraCategory
Observability
Observability
Stars
★ 5.7k
★ 4.4k
License
Apache-2.0
AGPL-3.0 (enterprise parts under a commercial license)
Install Command
curl -sL https://agentgateway.dev/install.sh | bash -s -- --install-path /usr/local/bin
docker pull archestra/platform:latest; docker run -p 9000:9000 -p 3000:3000 -e ARCHESTRA_QUICKSTART=true -v /var/run/docker.sock:/var/run/docker.sock -v archestra-postgres-data:/var/lib/postgresql/data -v archestra-app-data:/app/data archestra/platform;
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
AI Gateway, Multi-Agent Communication, LLM Proxy
AI Platform, AI Security, Kubernetes
03
Features
agentgateway01LLM Gateway: Route traffic to major LLM providers through a unified OpenAI-compatible API with budget controls, load balancing, and failover.
02MCP Gateway: Connect LLMs to tools and external data sources via MCP with OpenAPI integration and OAuth authentication.
03A2A Gateway: Enable secure agent-to-agent communication using A2A, with capability discovery, modality negotiation, and task collaboration.
04Guardrails: Multi-layered content filtering with regex, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor, and custom webhooks.
05Security & Observability: Provide authentication (JWT, API keys, OAuth), fine-grained RBAC, rate limiting, TLS, and OpenTelemetry metrics/logs/tracing.
archestra01Secure, MCP-native AI Platform for simplified enterprise AI usage.
02Private MCP registry with governance and ChatGPT-like chat capabilities.
03Kubernetes-native orchestration for managing AI servers and credentials.
04Advanced security features to prevent prompt injections and data exfiltration.
05Comprehensive cost monitoring, dynamic optimization, and observability tools.
04
Use Cases
agentgateway↳Managing and routing traffic to multiple LLM providers with a unified API and cost controls.
↳Enabling secure and standardized communication between AI agents and external tools/data sources.
↳Facilitating collaborative task execution among multiple AI agents across different environments.
↳Implementing intelligent inference routing for self-hosted models based on resource utilization.
↳Applying multi-layered content filtering and moderation for AI interactions to ensure safety and compliance.
archestra↳Centralized orchestration and secure management of AI models and data for platform teams.
↳Secure deployment and development of AI agents across the organization for developers.
↳Facilitating organization-wide AI adoption, cost reduction, and usage visibility for management.
05
Best For
agentgatewayEssentialTrending
archestraEssentialTrending
FAQ
FAQ
What is the difference between agentgateway and archestra?
Both agentgateway and archestra are in the Observability category. agentgateway has 5.7k stars, while archestra has 4.4k stars.
Which is better, agentgateway or archestra?
The best choice depends on your use case. Choose agentgateway if Managing and routing traffic to multiple LLM providers with a unified API and cost controls., and archestra if Centralized orchestration and secure management of AI models and data for platform teams..
Is agentgateway free or open source?
Yes, agentgateway is open source on GitHub (Apache-2.0).
Is archestra free or open source?
Yes, archestra is open source on GitHub (AGPL-3.0 (enterprise parts under a commercial license)).
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