- MCP Server
MCP Server
MCP server that provides tools for metadata retrieval from SharePoint and entity retrieval from a Neo4j knowledge graph using semantic similarity search.
Content
MCP Server
A Python-based server application that provides tools for metadata retrieval from SharePoint and entity retrieval from a Neo4j knowledge graph using semantic similarity search.
Features
- Metadata Retrieval: Fetches structured metadata from SharePoint's 'Documents' library
- Entity Retrieval: Queries a Neo4j knowledge graph using semantic similarity to find relevant entities and their relationships
- FastMCP Integration: Built on top of FastMCP framework for tool management and execution
Prerequisites
- Python 3.x
- Neo4j database
- SharePoint access credentials
- OpenAI API key (for semantic search)
Installation
- Clone the repository:
git clone <repository-url>
cd mcp-server
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Configure environment variables:
Create a
.envfile with the following variables:
SHAREPOINT_URL=
SHAREPOINT_USERNAME=
SHAREPOINT_PASSWORD=
SHAREPOINT_LIBRARY_NAME=
NEO4J_URI=
NEO4J_USER=
NEO4J_PASSWORD=
EMBEDDING_MODEL_ENDPOINT=
EMBEDDING_MODEL_KEY=
EMBEDDING_MODEL_API_VERSION=
EMBEDDING_MODEL_DEPLOYMENT_NAME=
EMBEDDING_MODEL_CHUNK_SIZE=
EMBEDDING_MODEL_DIMENSION=
EMBEDDING_MODEL_CHUNK_OVERLAP=
Usage
- Start the server:
python mcp_server.py
- The server provides two main tools:
metadata_retrieve: Retrieves structured metadata from SharePointentity_retrieve: Queries the knowledge graph using semantic similarity
Project Structure
.
├── mcp_server.py # Main server application
├── settings.py # Configuration management
├── services/ # Service implementations
│ ├── graph_store.py # Neo4j graph operations
│ └── sharepoint.py # SharePoint integration
├── requirements.txt # Project dependencies
└── .env # Environment variables
Dependencies
- langchain-mcp-adapters
- mcp[cli]
- langchain_openai
- pinecone
- langchain
- langchain_neo4j
- office365-rest-python-client
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