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MCP Agent

@Nhahan

Repository

About MCP Agent

MCP Agent is optimized using the ReWOO pattern, enabling even LLMs with fewer parameters to efficiently utilize MCP Server with minimal token consumption.

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-agent-nhahan": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Agent?

MCP Agent is a LangGraph agent based on the ReWOO (Reasoning WithOut Observation) pattern that reduces prompt complexity for small LLMs and integrates with the Model Context Protocol (MCP) server for efficient tool execution.

How to use MCP Agent?

Install dependencies, set environment variables as shown in .env.example, configure MCP servers in mcp.json, then run python main.py. The agent executes the ReWOO workflow through a series of LangGraph nodes.

Key features of MCP Agent

  • Implements the ReWOO pattern to minimize prompt complexity, especially for small LLMs.
  • Filters available tools to those most relevant for the current query.
  • Validates and automatically corrects execution plans on errors.
  • Manages evidence in a dictionary, referencing previous results with placeholders.
  • Orchestrates nine specialized LangGraph nodes for a structured workflow.
  • Designed for efficient interaction with any MCP-compatible server.

Use cases of MCP Agent

  • Automate multi-step reasoning tasks via MCP server tools.
  • Perform complex tool calls using small or resource-constrained language models.
  • Reduce token usage and prompt overloading compared to the ReAct pattern.
  • Validate tool plans before execution to catch errors early.

FAQ from MCP Agent

—

Comments

Basic information

Category

AI & Agents

Transports

stdio

Author

Nhahan

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