MCP Server

Name: MCP Server
Author: JanithSilva

@JanithSilva

关于 MCP Server

MCP server that provides tools for metadata retrieval from SharePoint and entity retrieval from a Neo4j knowledge graph using semantic similarity search.

#mcp-server #metadata-retrieval #knowledge-graph

基本信息

分类

记忆与知识

运行时

python

传输方式

stdio

发布者

JanithSilva

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-janithsilva": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

工具

未检测到工具

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 MCP Server?

A Python-based server that provides tools for retrieving metadata from SharePoint's 'Documents' library and querying a Neo4j knowledge graph using semantic similarity search. Built on the FastMCP framework, it is intended for applications needing structured document metadata and entity-relationship information.

How to use MCP Server?

Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, and configure environment variables in a .env file (including SharePoint credentials, Neo4j URI, and embedding model settings). Start the server with python mcp_server.py, then invoke the metadata_retrieve or entity_retrieve tools.

Key features of MCP Server

Retrieves structured metadata from SharePoint Documents library
Queries Neo4j knowledge graph with semantic similarity search
Built on FastMCP framework for tool management
Configurable via environment variables
Uses semantic embedding for entity retrieval

Use cases of MCP Server

Automating metadata extraction from SharePoint for document management
Finding relevant entities and relationships in a knowledge graph via natural language queries
Integrating document metadata with knowledge graph data for enhanced search
Enabling AI assistants to access structured information from both sources

FAQ from MCP Server

What systems does MCP Server integrate with?

SharePoint (Documents library) for metadata and Neo4j for knowledge graph entities. It also requires an embedding model API endpoint and key for semantic search.