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mcp-agent-tool-adapter

mcp-agent-tool-adapter

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github.com/serkanyasrAI & Agents6Updated 80w ago

About mcp-agent-tool-adapter

mcp-agent-tool-adapter turns MCP tools into agents built with Google ADK or LangGraph. It includes streaming and CLI interfaces, with an MCP client that manages server processes, sessions, tool adaptation, and cleanup.

Key features

  1. 01Google ADK agent support
  2. 02LangGraph ReAct agent support
  3. 03Streaming FastAPI interface
  4. 04CLI chat interfaces
  5. 05MCP server and session management

Use cases

  1. 01Run a CLI agent with configured MCP tools
  2. 02Choose Google ADK or LangGraph for tool use
  3. 03Serve an agent through streaming FastAPI

MCP support

The MCP client starts configured MCP servers, manages sessions, adapts their tools for Google ADK or LangGraph, and cleans up resources.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

mcp-agent-tool-adapter

From Protocol to Intelligence: Powering Agents with MCP.

license last-commit repo-top-language repo-language-count


📍 Overview

MCP Agent Tool Adapter enables modular tool invocation via the MCP protocol, and provides agents that can dynamically reason with tools using either Google ADK or LangGraph.

This project transforms MCP tools into:

  • 🤖 Google ADK-based agents with streaming FastAPI or CLI interfaces
  • 🧠 LangGraph-based agents that use ReAct + streaming tool planning

🧱 Project Structure

mcp-agent-tool-adapter/
├── mcp_client/                # Core client implementation (modular)
│   ├── client.py              # MCPClient & MCPServer
│   ├── tool_loader.py         # High-level async loader
│   └── types.py               # Shared type definitions
├── app_client_adk.py         # Google ADK agent + CLI chat
├── app_client_langgraph.py   # LangGraph agent + ReAct CLI chat
├── mcp_config.json           # Example MCP tool config
├── requirements.txt          # Dependencies
└── README.md

🚀 Getting Started

☑️ Prerequisites
  • Python 3.10+
⚙️ Installation
# Clone this repository
❯ git clone https://github.com/serkanyasr/mcp-agent-tool-adapter
❯ cd mcp-agent-tool-adapter

# Install dependencies
❯ pip install -r requirements.txt

🤖 Usage

Run Google ADK CLI agent:
❯ python app_client_adk.py
Run LangGraph ReAct CLI agent:
❯ python app_client_langgraph.py

Ensure your mcp_config.json defines tools like:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["@modular-protocol/filesystem"]
    }
  }
}

🧠 Tool Architecture

MCP tools are connected to agents through MCPClient, which handles:

  • Tool server spawning (via subprocess)
  • Session management
  • Tool adaptation (langgraph or Google ADK)
  • Cleanup

You can dynamically swap agent type by changing tool_type to "google" or "langgraph" in your app.


🧪 Development / Contributing

  • Fork the repo and create feature branches.
  • Submit a PR with a description of your changes.
  • Tag @serkanyasr in issues or PRs.

We welcome contributions in:

  • 🧩 new MCP tool adapters
  • 🧠 multi-agent LangGraph use cases
  • 🛠️ OpenAPI / streaming support

🎗 License

This project is licensed under the MIT License.For more details, refer to the LICENSE file.


Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.