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LANGGRAPH-MCP-AGENTS

LANGGRAPH-MCP-AGENTS

Local
github.com/serkanyasrAI & Agents6Updated 80w ago

About LANGGRAPH-MCP-AGENTS

LANGGRAPH-MCP-AGENTS connects MCP tools to agents built with LangGraph or Google ADK. It is for developers who want CLI or streaming agent interfaces and configurable tool-server sessions.

Key features

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

Use cases

  1. 01Build a LangGraph agent that reasons with MCP tools
  2. 02Run a Google ADK agent from the CLI
  3. 03Switch agent type through app configuration

MCP support

The project uses an MCP client to spawn tool servers, manage sessions, adapt tools for LangGraph or Google ADK, and clean up connections.

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.