Design · MODEL CONTEXT PROTOCOL

Srish ty MCP Testing interface for LLMs

MCP Testing interface for LLMs

连接能力

Srish ty MCP Testing interface for LLMs 为 AI Agent 提供什么

  • In-memory storage of user contexts
  • Context management with last 5 prompts
  • RESTful API endpoints
  • TypeScript support
  • Install dependencies:
  • Start the development server:
  • `npm run dev`: Start development server with hot reload
  • `npm run build`: Build TypeScript files
  • `npm start`: Run built files

安全

MCP 收录不等于安全审核

MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。

README

仓库文档

Memory Context Provider (MCP) Server

A server that manages context for LLM interactions, storing and providing relevant context for each user.

Features

  • In-memory storage of user contexts
  • Context management with last 5 prompts
  • RESTful API endpoints
  • TypeScript support

Setup

  1. Install dependencies:

    npm install
  2. Start the development server:

    npm run dev

API Endpoints

POST /context/:userId

Add a new prompt to user's context and get updated context.

Request body:

{
  "prompt": "Your prompt here"
}

Response:

{
  "context": "Combined context from last 5 prompts"
}

GET /context/:userId

Get current context for a user.

Response:

{
  "context": "Current context"
}

DELETE /context/:userId

Clear context for a user.

Response:

{
  "message": "Context cleared"
}

Development

  • npm run dev: Start development server with hot reload
  • npm run build: Build TypeScript files
  • npm start: Run built files
在 GitHub 查看 README

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