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官方说明3 个来源MCP 服务3 天前
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LLM-agnostic platform for agent building & testing
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来源明细
收录自 e2b-dev/awesome-ai-agents 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-14 · 最近见到 2026-10-16 · 共见到 5 次 · 被 3 个来源列出
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综合分 303 · 3 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-10-14;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

AgentForge

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**AgentForge** is a low-code framework for rapid development, testing, and iteration of AI-powered autonomous agents and cognitive architectures. Its core concepts - flexible **Agents**, declarative **Cogs**, and optional **Memory** - support both simple first runs and sophisticated multi-agent orchestration.
Compatible with a range of LLM models—including OpenAI, Google's Gemini, Anthropic's Claude, and local models via Ollama or LMStudio—AgentForge lets you run different models for different agents as needed.
If you are new to AgentForge, start with the public docs hub before opening schemas, memory, storage, subclassing, utilities, or legacy Tools/Actions references.
---
Table of Contents
1. Start Here
2. Features
3. Documentation
4. Contributing
5. Contact Us
6. License
---
Start Here
Start with **AgentForge Documentation**.
The docs hub gives the recommended order for the first smoke test, the first real Codex-backed model run, the beginner Cog examples, and the advanced references.
---
Features
Build agents and cognitive architectures (multi-agent systems) with:
- **Declarative Cogs**: Orchestrate multi-agent workflows, branching logic, and memory using simple YAML files. Cogs are the primary way to compose agents into complex, reusable workflows.
- **Customizable Agents**: Define agents using YAML prompt templates and configuration.
- **Integrated Memory**: Add contextual memory to agents and cogs for coherent, context-aware interactions. Memory nodes are declared in Cogs and made available to agents automatically.
- **Personas**: Configure agent identity, style, and context using persona YAML files.
- **Dynamic Prompt Templates**: Use flexible prompt templates that adapt to various contexts and memory.
- **LLM Agnostic**: Run different agents with different LLMs as needed.
- **On-The-Fly Prompt Editing**: Modify prompts in real-time without restarting the system.
- **OpenAI, Google & Anthropic API Support**: Integrate with popular LLM APIs.
- **Open-Source Model Support**: Leverage local models through Ollama and LMStudio.
---
Documentation
- **Docs Hub**: Canonical public navigation for first runs and reference material.
- **Quickstart**: Install, scaffold .agentforge/, and run a no-credential debug smoke test.
来源
awesome · https://github.com/DataBassGit/AgentForge
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