Cloud MCP Calculator
A cloud-deployable math tool server that provides calculator capabilities to local LLM agents via the Model Context Protocol and Server-Sent Events. It allows instructors to host a centralized calculation engine that students can connect to from their local development environments.
README
Cloud MCP Calculator: Student & Instructor Guide
This repository contains a cloud-deployable math tool server using the Model Context Protocol (MCP) via Server-Sent Events (SSE). This architecture allows students to connect their local local LLM agents (via VS Code Continue) to a centralized, instructor-managed tool.
Distributed Architecture
The following diagram shows how the system is distributed between the instructor's cloud infrastructure and the students' local machines.
graph TB
subgraph "Cloud Infrastructure (Instructor)"
VM[Cloud Virtual Machine]
Docker[Docker Container]
Uvicorn[Uvicorn / SSE Server]
CalcTool[Calculator Logic]
VM --> Docker
Docker --> Uvicorn
Uvicorn --> CalcTool
end
subgraph "Student Machine"
VSCode[VS Code + Continue]
LLM[Local LLM / Ollama]
NB[01_math_agent.ipynb]
end
VSCode -- "HTTP-SSE / Port 8080" --> Uvicorn
NB -- "Standard Logic" --> OpenAI[OpenAI / API]
Protocol Interaction Flow
When a student asks a math question, the following exchange occurs via the SSE protocol:
sequenceDiagram
participant S as Student (VS Code)
participant C as Cloud server (VM)
participant T as Calculator Tool
S->>C: GET /sse (Connect)
C-->>S: SSE Stream Opened
S->>C: POST /sse?sessionId=... (Initialize)
C-->>S: JSON-RPC (Capabilites & ServerInfo)
S->>C: POST /sse (tools/call: calculate)
C->>T: eval(expression)
T-->>C: Result (e.g., "42")
C-->>S: JSON-RPC Result
S->>S: Display "The answer is 42."
Student Setup (config.yaml)
To connect to the cloud tool, update your ~/.continue/config.yaml as follows:
mcpServers:
- name: cloud-calc
type: sse
url: http://<YOUR-VM-PUBLIC-IP>:8080/sse
experimental:
autoExecuteTools: true
Instructor Setup (Makefile)
Use the provided Makefile on your VM to manage the service easily:
| Command | Action |
|---|---|
make build |
Builds the mcp-calculator Docker image. |
make run |
Starts the server in background (detached) on port 8080. |
make logs |
Follows the live server logs (useful for debugging student connections). |
make stop |
Gracefully stops and removes the running container. |
VM Security Note:
Ensure your VM's Cloud Firewall (Security Group) allows Inbound TCP traffic on Port 8080.
Debug:
curl -v http://YOUR-VM-PUBLIC-IP>:8080/sse
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。