MCP Servers

模型上下文协议服务器、框架、SDK 和模板的综合目录。

M
Model Context Protocol
作者 @Ritwikkkk

This repo will be consisting of some Agentic AI projects with MCP server.

创建于 12/24/2025
更新于 1 day ago
Repository documentation and setup instructions

model-context-protocol

This repo consists of a basic agent structure by using tool from Bright Data MCP server.

In the stock recommender code I was facing this below mentioned error even after trying lots of things. But finally Gemini 3.0 gave me the solution.

The error NotImplementedError: StructuredTool does not support sync invocation occurs because you are using Model Context Protocol (MCP) tools (which are inherently asynchronous) inside a LangGraph workflow that is attempting to execute them synchronously.

Even though your run_agent function is async, the internal supervisor.stream loop and the way the agents are compiled are defaulting to synchronous execution for the tool calls.

The Solution: Await the Stream To fix this, you need to change how you iterate through the supervisor's results. LangGraph provides an async streaming method (astream) for exactly this scenario.

Here are the specific changes you need to make:

  1. Use astream instead of stream Replace your synchronous for loop with an async for loop.

Change this:

Python

for chunk in supervisor.stream( {"messages": [{"role": "user", "content": query}]}, ): pretty_print_messages(chunk, last_message=True) To this:

Python

async for chunk in supervisor.astream( {"messages": [{"role": "user", "content": query}]}, # subgraphs=True # Optional: add if you want to see inner agent steps ): pretty_print_messages(chunk, last_message=True)

快速设置
此服务器的安装指南

安装包 (如果需要)

uvx model-context-protocol

Cursor 配置 (mcp.json)

{ "mcpServers": { "ritwikkkk-model-context-protocol": { "command": "uvx", "args": [ "model-context-protocol" ] } } }