🚀 Light MCP Agents
@nicozumarraga
🚀 Light MCP Agents について
Lightweight, composable framework for building muti-agent systems with Model Context Protocol (MCP)
概要
What is 🚀 Light MCP Agents?
Light MCP Agents is a lightweight Python framework for building and orchestrating AI agents using the Model Context Protocol (MCP). It enables configuration‑driven creation of hierarchical agent systems where specialized agents delegate tasks, share capabilities, and collaborate to solve complex problems.
How to use 🚀 Light MCP Agents?
Clone the repository, create a Python virtual environment, install dependencies with pip install -r requirements.txt, then run an agent via python src/agent/agent_runner.py --config <config_file_path>. For multi‑agent setups, start agents in server mode (--server-mode) and connect orchestrators via their configuration files. Agents can also be configured to run inside Claude Desktop by adding their runner command to claude_desktop_config.json.
Key features of 🚀 Light MCP Agents
- Configuration‑driven agent creation, no extra code required
- Hierarchical agent architecture with ability to delegate tasks
- Capabilities that invoke full LLM reasoning on demand
- Automatic tool aggregation from lower‑level agents
- Server mode allows agents to be used by other agents
- Works with any MCP server and any LLM provider
Use cases of 🚀 Light MCP Agents
- Building a research assistant that delegates web searching and document summarization to specialized sub‑agents
- Creating an orchestrator agent that coordinates multiple domain‑specific agents for complex workflows
- Rapidly prototyping multi‑agent systems using only JSON configuration files
FAQ from 🚀 Light MCP Agents
How does 🚀 Light MCP Agents differ from other agent frameworks?
It is a lightweight, configuration‑driven framework built entirely on the MCP protocol. Agents can be arranged hierarchically, and each agent can expose high‑level capabilities that trigger its own LLM reasoning and tool use.
Can I use my own LLM or MCP servers?
Yes. You configure the LLM provider (e.g., Groq) and API key in the agent’s JSON config, and you can connect any MCP server (e.g., Brave Search, Kanye‑mcp) by specifying its command and arguments.
How do I create a multi‑agent system?
Define a “server‑mode” agent (e.g., a research agent) with its own config and run it with --server-mode. Then create an orchestrator agent that lists that agent as a server in its configuration. The orchestrator can then delegate tasks via the sub‑agent’s capabilities.
Can I run agents in Claude Desktop?
Yes. Add your agent runner command (with --server-mode) to Claude Desktop’s claude_desktop_config.json under the mcpServers section. Claude will then be able to use your agent’s tools and capabilities.
Is there a limit to agent recursion?
A recursion limit can be configured. The architecture supports recursive reasoning, meaning an agent can call another agent, which can call others, and so on, until the limit is reached.
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