--- title: "plano" type: "tool" slug: "katanemo-plano" canonical_url: "https://www.graphcanon.com/tools/katanemo-plano" github_url: "https://github.com/katanemo/plano" homepage_url: "https://planoai.dev" stars: 6684 forks: 442 primary_language: "Rust" license: "Apache-2.0" categories: ["llm-frameworks", "developer-tools"] tags: ["agentic-applications", "llm-routing", "moderation", "observability", "ai-gateway", "llm-inference", "envoyproxy", "smart-routing"] updated_at: "2026-07-07T18:37:54.63482+00:00" --- # plano > Plano is an AI-native proxy and data plane for agentic apps with built-in orchestration, safety, observability, and smart LLM routing. Plano centralizes agent routing and orchestration, provides rich observability signals, ensures safety through moderation policies, and supports smart LLM routing. It allows developers to focus on the core logic of their agentic applications. ## Facts - Repository: https://github.com/katanemo/plano - Homepage: https://planoai.dev - Stars: 6,684 · Forks: 442 · Open issues: 132 · Watchers: 51 - Primary language: Rust - License: Apache-2.0 - Last pushed: 2026-07-07T17:04:49+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) - [Developer Tools](/categories/developer-tools.md) ## Tags agentic-applications, llm-routing, moderation, observability, ai-gateway, llm-inference, envoyproxy, smart-routing ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [JavaGuide](/tools/snailclimb-javaguide.md) - Snailclimb/JavaGuide: 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发 (★ 156,863) - [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 144,575) - [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. (★ 116,702) ## README (excerpt) ```text
Plano Logo
_The AI-native proxy server and data plane for agentic apps._

Plano pulls out the rote plumbing work and decouples you from brittle framework abstractions, centralizing what shouldn’t be bespoke in every codebase - like agent routing and orchestration, rich agentic signals and traces for continuous improvement, guardrail filters for safety and moderation, and smart LLM routing APIs for model agility. Use any language or AI framework, and deliver agents faster to production. [Quickstart Guide](https://docs.planoai.dev/get_started/quickstart.html) • [Build Agentic Apps with Plano](#Build-Agentic-Apps-with-Plano) • [Documentation](https://docs.planoai.dev) • [Contact](#Contact) Star ⭐️ the repo if you found Plano useful — new releases and updates land here first.
# Overview Building agentic demos is easy. Shipping agentic applications safely, reliably, and repeatably to production is hard. After the thrill of a quick hack, you end up building the “hidden middleware” to reach production: routing logic to reach the right agent, guardrail hooks for safety and moderation, evaluation and observability glue for continuous learning, and model/provider quirks scattered across frameworks and application code. Plano solves this by moving core delivery concerns into a unified, out-of-process dataplane. - **🚦 Orchestration:** Low-latency orchestration between agents; add new agents without modifying app code. - **🔗 Model Agility:** Route [by model name, alias (semantic names) or automatically via preferences](#use-plano-as-a-llm-router). - **🕵 Agentic Signals™:** Zero-code capture of [Signals](https://docs.planoai.dev/concepts/signals.html) plus OTEL traces/metrics across every agent. - **🛡️ Moderation & Memory Hooks:** Build jailbreak protection, add moderation policies and memory consistently via [Filter Chains](https://docs.planoai.dev/concepts/filter_chain.html). Plano pulls rote plumbing out of your framework so you can stay focused on what matters most: the core product logic of your agentic applications. Plano is backed by [industry-leading LLM research](https://planoai.dev/research) and built on [Envoy](https://envoyproxy.io) by its core contributors, who built critical infrastructure at scale for modern worklaods. **High-Level Network Sequence Diagram**: **Jump to our [docs](https://docs.planoai.dev)** to learn how you can use Plano to improve the speed, safety and obervability of your agentic applications. > [!IMPORTANT] > Plano and the Plano family of LLMs (like Plano-Orchestrator) are hosted free of charge in the US-central region to give you a great first-run developer experience of Plano. To scale and run in production, you can either run these LLMs locally or contact us on [Discord](https://discord.gg/pGZf2gcwEc) for API keys. --- ## Build Agentic Apps with Plano Plano handles **orchestration, model management, and observability** as modular building blocks - letting you configure only what you need (edge proxying for agentic orchestration and guardrails, or LLM routing from your services, or both together) to fit cleanly into existing architectures. Below is a simple multi-agent travel agent built with Plano that showcases all three core capabilities > 📁 **Full working code:** See [`demos/agent_orchestration/travel_agents/`](demos/agent_orchestration/travel_agents/) for complete weather and flight agents you can run locally. ### 1. Define Your Agents in YAML ```yaml # config.yaml version: v0.3.0 # What you declare: Agent URLs and natural language descriptions # What you don't write: Intent classifiers, routing logic, model fallbacks, provider adapters, or tracing instrumentation agents: - id: weather_agent url: http://localhost:10510 - id: flight_agent url: http://localhost:10520 model_providers: - model: openai/gpt ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/katanemo-plano`](/api/graphcanon/tools/katanemo-plano) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_