Trpc Agent Go
A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, evaluation, and observability.
安装配置
暂未识别到可直接复制的 MCP 配置，请查看 GitHub README。后台管理员可以补充配置。
README 摘要
English | [中文](README.zh_CN.md) # tRPC-Agent-Go [](https://pkg.go.dev/trpc.group/trpc-go/trpc-agent-go) [](https://goreportcard.com/report/github.com/trpc-group/trpc-agent-go) [](https://github.com/trpc-group/trpc-agent-go/blob/main/LICENSE) [](https://github.com/trpc-group/trpc-agent-go/releases) [](https://github.com/trpc-group/trpc-agent-go/actions/workflows/prc.yml) [](https://app.codecov.io/gh/trpc-group/trpc-agent-go/tree/main) [](https://trpc-group.github.io/trpc-agent-go/) **A powerful Go framework for building intelligent agent systems** that transforms how you create AI applications. Build autonomous agents that think, remember, collaborate, and act with unprecedented ease. **Why tRPC-Agent-Go?** - **Intelligent Reasoning**: Advanced hierarchical planners and multi-agent orchestration - **Rich Tool Ecosystem**: Seamless integration with external APIs, databases, and services - **Persistent Memory**: Long-term state management and contextual awareness - **Multi-Agent Collaboration**: Chain, parallel, and graph-based agent workflows - **GraphAgent**: Type-safe graph workflows with multi-conditional routing, functionally equivalent to LangGraph for Go - **Agent Skills**: Reusable `SKILL.md` workflows with safe execution - **Artifacts**: Versioned storage for files produced by agents and tools - **Prompt Caching**: Automatic cost optimization with 90% savings on cached content - **Evaluation & Benchmarks**: Eval sets + metrics to measure quality over time - **UI & Server Integration**: AG-UI (Agent-User Interaction), and Agent-to-Agent (A2A) interoperability - **Production Ready**: Built-in telemetry, tracing, and enterprise-grade reliability - **High Performance**: Optimized for scalability and low latency ## Use Cases **Perfect for building:** - **Customer Support Bots** - Intelligent agents that understand context and solve complex queries - **Data Analysis Assistants** - Agents that query databases, generate reports, and provide insights - **DevOps Automation** - Smart deployment, monitoring, and incident response systems - **Business Process Automation** - Multi-step workflows with human-in-the-loop capabilities - **Research & Knowledge Management** - RAG-powered agents for document analysis and Q&A ## Key Features ### Multi-Agent Orchestration ```go // Chain agents for complex workflows pipeline := chainagent.New("pipeline", chainagent.WithSubAgents([]agent.Agent{ analyzer, processor, reporter, })) // Or run them in parallel parallel := parallelagent.New("concurrent", parallelagent.WithSubAgents(tasks)) ``` ### Advanced Memory System ```go // Persistent memory with search memory := memorysvc.NewInMemoryService() agent := llmagent.New("assistant", llmagent.WithTools(memory.Tools()), llmagent.WithModel(model)) // Memory service managed at runner level runner := runner.NewRunner("app", agent, runner.WithMemo...
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