# agentoven **Repository Path**: wurulan/agentoven ## Basic Information - **Project Name**: agentoven - **Description**: AgentOven is a **framework-agnostic agent control plane** that standardizes how AI agents are built, deployed, observed, and orchestrated across an enterprise. Think of it as a **clay oven** πΊ β you put in raw ingredients (models, tools, data, prompts) and **production-ready agents come out the chimney**. - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-04-15 - **Last Updated**: 2026-05-12 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README
Bake production-ready AI agents.
The open-source enterprise agent control plane with native A2A + MCP support.
Documentation β’ Quickstart β’ Discord β’ Discussions β’ Contributing
--- ## What is AgentOven? AgentOven is a **framework-agnostic agent control plane** that standardizes how AI agents are built, deployed, observed, and orchestrated across an enterprise. Think of it as a **clay oven** πΊ β you put in raw ingredients (models, tools, data, prompts) and **production-ready agents come out the chimney**. ### The Problem - Agents are built ad-hoc with no consistency - No governance, audit trail, or cost visibility - Locked into single vendors (Databricks, Azure, LangChain) - Multi-agent workflows are stitched together manually - No standard protocol for agent-to-agent collaboration ### The Solution AgentOven provides a unified control plane with: | Capability | Description | |---|---| | πΊ **Agent Registry** | Version, discover, and manage agents as first-class resources | | π **Model Router** | Intelligent routing across providers with fallback, cost optimization | | π€ **A2A Native** | [Agent-to-Agent protocol](https://github.com/google/A2A) built-in from day 1 | | π§ **MCP Gateway** | [Model Context Protocol](https://modelcontextprotocol.io/) for tool/data integration | | π **Observability** | OpenTelemetry tracing on every invocation, cost & latency dashboards | | π **Workflow Engine** | DAG-based multi-agent orchestration via A2A task lifecycle | | π **Prompt Studio** | Versioned prompt management with diff view and A/B variants | | π¬ **Sessions** | Multi-turn chat sessions with history, thinking mode, and streaming | | π‘οΈ **Guardrails** | Pre/post processing content filters and safety checks | | π§ͺ **Evaluation** | Automated evals with LLM judges and regression detection | | π° **Cost Tracking** | Per-request token counting, tenant-level chargeback | | π **Governance** | Pluggable auth (API keys, service accounts, SSO), RBAC, audit logs | | π **RAG Pipelines** | 5 retrieval strategies with vector stores and embedding management | ## Architecture ``` βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β AgentOven Control Plane β β (Registry Β· Router Β· RBAC Β· Cost Β· Tenancy) β β Go ββββββββββββββββββββββββ¬βββββββββββββββββββββββββββββββββββββββ€ β A2A Gateway β MCP Gateway β β (Agent β Agent) β (Agent β Tools/Data) β β Go ββββββββββββββββββββββββ΄βββββββββββββββββββββββββββββββββββββββ€ β AgentOven Runtime β β (Execute Β· Instrument Β· Route Β· Enforce Policies) β β Rust βββββββββββ¬ββββββββββ¬βββββββββββ¬βββββββββββ¬ββββββββββββββββββββ€ βLangGraphβ CrewAI βOpenAI SDKβ AutoGen β Custom Agents β βββββββββββ΄ββββββββββ΄βββββββββββ΄βββββββββββ΄ββββββββββββββββββββ ``` ## Quick Start ### Install the CLI ```bash # macOS brew install agentoven/tap/agentoven # Cargo cargo install agentoven-cli # Or download the binary curl -fsSL https://agentoven.dev/install.sh | sh ``` ### Install the Python SDK ```bash pip install agentoven ``` ### Install the TypeScript SDK ```bash npm install @agentoven/sdk ``` ### Bake your first agent ```bash # Initialize a project agentoven init --name my-agent --framework openai-sdk # Set up a model provider agentoven provider add my-openai --kind openai --api-key $OPENAI_API_KEY # Register an agent agentoven agent register summarizer \ --description "Summarizes documents with citations" \ --model-provider my-openai \ --model-name gpt-4o \ --system-prompt "You are a document summarizer." # Bake (deploy) the agent agentoven agent bake summarizer # Test it interactively agentoven agent test summarizer --interactive ``` ### Or use the Python SDK **Simple β single model, no extras:** ```python from agentoven import Agent, AgentOvenClient agent = Agent("summarizer", description="Summarizes documents with citations", model_provider="my-openai", model_name="gpt-4o", system_prompt="You are a document summarizer.", ) client = AgentOvenClient() client.register(agent) client.bake(agent, environment="production") ``` **Advanced β multi-model fallback, tools, and MCP:** ```python from agentoven import Agent, Ingredient, AgentOvenClient agent = Agent("summarizer", description="Summarizes documents with citations", ingredients=[ Ingredient.model("gpt-4o", provider="my-openai"), Ingredient.model("claude-sonnet", provider="anthropic", role="fallback"), Ingredient.tool("document-reader", protocol="mcp"), Ingredient.prompt("system", text="You are a document summarizer."), ], ) client = AgentOvenClient() client.register(agent) client.bake(agent, environment="production") # The agent is now discoverable via A2A # Other agents can find it at: # /.well-known/agent-card.json ``` ### Multi-Agent Recipes ```python from agentoven import Recipe, Step, AgentOvenClient # A Recipe is a multi-agent workflow recipe = Recipe("document-review", steps=[ Step("planner", agent="task-planner", timeout="30s"), Step("researcher", agent="doc-researcher", parallel=True), Step("summarizer", agent="summarizer"), Step("reviewer", agent="quality-reviewer"), Step("approval", human_gate=True, notify=["team-leads"]), ], ) # Bake the recipe via the client client = AgentOvenClient() client.bake(recipe, input='{"document_url": "https://..."}') ``` --- ## CLI Reference The `agentoven` CLI provides **55+ commands** across **13 command groups** for complete control of your agent infrastructure. ### Global Flags ``` --urlπΊ Baked with care by the AgentOven community.