Project Description MCP Server

@pizzaeueu

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

pizzaeueu

关于 Project Description MCP Server

The proxy enables integration between OpenAI chat models and local MCP servers via Function Calling, allowing custom PII checks for sensitive data verification

Project Description MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

Project Description MCP Server 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Project Description?

Project Description is a proxy that integrates OpenAI chat models with local MCP servers via function calling, adding custom PII checks for sensitive data verification. It is designed for users who need to control whether sensitive information retrieved from MCP tools is shared with the language model.

How to use Project Description?

Set your OpenAI API key in the OPEN_AI_API_KEY variable and an absolute path to the shared folder in the SHARED_DIRECTORY_ABSOLUTE_PATH variable in the Docker Compose file, then run docker compose up. Open http://localhost:4173/ and start chatting with the model. By default, it works with the filesystem MCP server (pre‑installed as a Docker image), but you can configure other MCP servers by editing data/McpConfig.conf.

Key features of Project Description

Enables OpenAI models to call tools on local MCP servers.
Runs regex‑based PII checks on data retrieved from MCP servers.
Asks users for permission before sharing sensitive data with the LLM.
Stateful with in‑memory persistence (workflows lost on crash/restart).
No authentication mechanism, no metrics, no strict SLAs.
PII detection supports English language only.

Use cases of Project Description

Safely use MCP file‑system tools with OpenAI without leaking sensitive content.
Review and approve or deny sharing of detected PII before it reaches the LLM.
Prototype integrations between OpenAI and custom MCP servers in a local environment.

常见问题

What does Project Description do differently from a direct MCP integration?

It adds a PII verification layer between MCP tool results and the LLM, prompting the user to allow or block sharing of sensitive data before the conversation continues.

What dependencies or runtime are required?

OpenAI chat models with tool‑calling support, a Docker environment, and an MCP server (e.g., the filesystem server installed as a Docker image).

Where does user data live?

User data is stored in‑memory; it is lost on crash or restart, and the app is not horizontally scalable.

What are the known limits of Project Description?

PII detection only works for English. If the data retrieved from MCP servers exceeds the LLM’s context window, the app returns an error and stops the dialog. Adding a new MCP server requires a restart.

What transport or authentication does it use?

The proxy does not implement any authentication mechanism. It communicates with MCP servers via the MCP Java SDK and with OpenAI via the OpenAI Java SDK using function calling.

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