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Flexible GraphRAG MCP Server

Model Context Protocol (MCP) server for Flexible GraphRAG system with optimized configurations for Claude Desktop and MCP Inspector.

Quick Start

1. Choose Your Platform & Method

Platform Recommended Alternative Why
Windows pipx uvx Clean system install vs. no install needed
macOS pipx uvx Clean system install vs. no install needed

2. Install

cd flexible-graphrag-mcp
pipx install .

uvx (No installation)

# Auto-installs when first used
uvx flexible-graphrag-mcp

3. Configure Claude Desktop

Copy the appropriate config file to your Claude Desktop configuration:

Windows

  • Config location: %APPDATA%\Claude\claude_desktop_config.json
  • pipx: Use claude-desktop-configs/windows/pipx-config.json
  • uvx: Use claude-desktop-configs/windows/uvx-config.json

macOS

  • Config location: ~/Library/Application Support/Claude/claude_desktop_config.json
  • pipx: Use claude-desktop-configs/macos/pipx-config.json
  • uvx: Use claude-desktop-configs/macos/uvx-config.json

4. Test Installation

Restart Claude Desktop and test:

@flexible-graphrag Check system status

Configuration Files

Claude Desktop Configs

claude-desktop-configs/
├── windows/
│   ├── pipx-config.json    # Windows + pipx
│   └── uvx-config.json     # Windows + uvx
└── macos/
    ├── pipx-config.json    # macOS + pipx
    └── uvx-config.json     # macOS + uvx

mcp-inspector/
├── pipx-stdio-config.json  # MCP Inspector + pipx (stdio - try first)
├── pipx-http-config.json   # MCP Inspector + pipx (HTTP - fallback)
├── uvx-stdio-config.json   # MCP Inspector + uvx (stdio - try first)
└── uvx-http-config.json    # MCP Inspector + uvx (HTTP - fallback)

Key Differences

Windows Configs

  • Include Unicode environment variables (PYTHONIOENCODING, PYTHONLEGACYWINDOWSSTDIO)
  • Prevent Unicode encoding errors with emojis and special characters

macOS Configs

  • Clean and simple - no special environment variables needed
  • Standard MCP protocol over stdio

MCP Inspector Configs

  • stdio configs: Standard MCP protocol - try these first
  • http configs: HTTP transport fallback if stdio has issues (like proxy problems)
  • HTTP mode runs on port 3001 by default (configurable with --port argument)
  • Platform-independent - works on Windows, macOS, and Linux

Installation Methods

Advantages: - ✅ Clean system-level installation - ✅ Isolated dependencies - ✅ Simple flexible-graphrag-mcp command - ✅ Automatic PATH management

Installation:

cd flexible-graphrag-mcp
pipx install .

Update:

pipx reinstall flexible-graphrag-mcp

uvx (Alternative)

Advantages: - ✅ No installation required - ✅ Automatic dependency management - ✅ Always runs latest version - ✅ Great for testing

Usage:

uvx flexible-graphrag-mcp

Prerequisites

Backend Server Required

The MCP server communicates with the FastAPI backend, so you must have it running:

cd flexible-graphrag
uv run uvicorn main:app --host 0.0.0.0 --port 8000

Environment Configuration

Ensure your .env file is properly configured in the main project directory:

# Neo4j Configuration
NEO4J_URI=bolt://localhost:7687
NEO4J_USERNAME=neo4j
NEO4J_PASSWORD=your-password
NEO4J_DATABASE=neo4j

# LLM Configuration
OPENAI_API_KEY=your-key
LLM_PROVIDER=openai
EMBEDDING_PROVIDER=openai

HTTP Mode for MCP Inspector

For debugging with MCP Inspector, the server supports HTTP transport:

# Using pipx
flexible-graphrag-mcp --http --port 3001

# Using uvx  
uvx flexible-graphrag-mcp --http --port 3001

# Custom port
flexible-graphrag-mcp --http --port 8080

The HTTP mode is automatically configured in the mcp-inspector/ config files and works better than stdio for debugging complex MCP interactions.

Available Tools

  • get_system_status() - System status and configuration
  • ingest_documents() - Ingest documents from 13 data sources (all support skip_graph; filesystem/Alfresco/CMIS use paths; Alfresco also supports nodeDetails list)
  • ingest_text(content, source_name) - Ingest custom text content
  • search_documents(query, top_k) - Hybrid search for document retrieval
  • query_documents(query, top_k) - AI-generated answers from documents
  • test_with_sample() - Quick test with sample text
  • check_processing_status(processing_id) - Check async operation status
  • get_python_info() - Python environment information
  • health_check() - Backend connectivity check

Tool Details

ingest_documents

Ingest documents from various sources into the knowledge graph.

Parameters: - data_source (string, default: "filesystem"): Type of data source - Options: filesystem, cmis, alfresco, web, wikipedia, youtube, s3, gcs, azure_blob, onedrive, sharepoint, box, google_drive - paths (string, optional): File path(s) to process (for filesystem, Alfresco, and CMIS sources) - Single path: "/path/to/file.pdf" - Multiple paths (JSON array): ["file1.pdf", "file2.docx"] - skip_graph (boolean, default: false): Skip knowledge graph extraction on a per-ingest basis for faster performance (vector + search only) - cmis_config (string, optional): CMIS configuration as JSON string - alfresco_config (string, optional): Alfresco configuration as JSON string (also supports nodeDetails list for multi-select) - web_config (string, optional): Web page configuration as JSON string - wikipedia_config (string, optional): Wikipedia configuration as JSON string - youtube_config (string, optional): YouTube configuration as JSON string - s3_config (string, optional): Amazon S3 configuration as JSON string - gcs_config (string, optional): Google Cloud Storage configuration as JSON string - azure_blob_config (string, optional): Azure Blob Storage configuration as JSON string - onedrive_config (string, optional): Microsoft OneDrive configuration as JSON string - sharepoint_config (string, optional): Microsoft SharePoint configuration as JSON string - box_config (string, optional): Box configuration as JSON string - google_drive_config (string, optional): Google Drive configuration as JSON string

Example - Basic filesystem with skip_graph:

{
  "data_source": "filesystem",
  "paths": "[\"./sample-docs/cmispress.txt\", \"./sample-docs/space-station.txt\"]",
  "skip_graph": true
}

Example - CMIS with single path:

{
  "data_source": "cmis",
  "paths": "[\"/Shared/GraphRAG/cmispress.txt\"]",
  "cmis_config": "{\"url\": \"https://cmis.example.com\", \"username\": \"admin\", \"password\": \"password\", \"folder_path\": \"/Shared/GraphRAG\"}"
}

Example - Alfresco with single path:

{
  "data_source": "alfresco",
  "paths": "[\"/Shared/GraphRAG/space-station.txt\"]",
  "alfresco_config": "{\"url\": \"https://alfresco.example.com\", \"username\": \"admin\", \"password\": \"password\", \"path\": \"/Shared/GraphRAG\"}"
}

Example - Alfresco with nodeDetails (multi-select from ACA):

{
  "data_source": "alfresco",
  "alfresco_config": "{\"url\": \"https://alfresco.example.com\", \"username\": \"admin\", \"password\": \"password\", \"nodeDetails\": [{\"id\": \"abc123\", \"name\": \"doc1.pdf\", \"path\": \"/Shared/GraphRAG/doc1.pdf\", \"isFile\": true, \"isFolder\": false}], \"recursive\": false}"
}

Example - Amazon S3:

{
  "data_source": "s3",
  "s3_config": "{\"bucket_name\": \"my-bucket\", \"prefix\": \"documents/\", \"access_key\": \"AKIAIOSFODNN7EXAMPLE\", \"secret_key\": \"wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\", \"region_name\": \"us-east-1\"}"
}

Example Usage

Basic Document Ingestion

@flexible-graphrag Please ingest documents from C:/Documents/research

Fast Ingestion (Skip Graph)

@flexible-graphrag Ingest from ./sample-docs/ with skip_graph=true for faster processing (works with all data sources)

Alfresco Multi-Select

@flexible-graphrag Ingest from Alfresco with this config: {"url": "https://alfresco.example.com", "username": "admin", "password": "password", "nodeDetails": [{"id": "abc123", "name": "report.pdf", "path": "/Shared/Reports/report.pdf", "isFile": true, "isFolder": false}]}

Custom Text Processing

@flexible-graphrag Ingest this text: "Claude is an AI assistant created by Anthropic."

Search and Q&A

@flexible-graphrag Search for "machine learning algorithms" in the documents
@flexible-graphrag What are the main conclusions from the research papers?

Async Processing

@flexible-graphrag Check processing status for ID abc123

Troubleshooting

Common Issues

pipx Command Not Found

# Install pipx
python -m pip install --user pipx
pipx ensurepath

uvx Command Not Found

# Install uvx via uv
uv tool install uvx

Unicode Errors on Windows

  • Windows configs include required environment variables automatically
  • If issues persist, check that you're using the correct Windows config file

Backend Connection Error

  • Ensure FastAPI backend is running on localhost:8000
  • Check that .env file is properly configured
  • Test backend directly: curl http://localhost:8000/api/health

Claude Desktop Not Recognizing Server

  • Restart Claude Desktop after config changes
  • Check config file path and JSON syntax
  • Verify command exists: run flexible-graphrag-mcp or uvx flexible-graphrag-mcp in terminal

Development

Test Scripts

# Windows
.\test-installation.ps1

# macOS/Linux
./test-installation.sh

These scripts test both installation methods and help verify everything works correctly.

Adding New Tools

  1. Add tool function to main.py with @mcp.tool() decorator
  2. Update tool list in README
  3. Test with MCP Inspector for debugging

MCP Inspector Integration

Use the configs in mcp-inspector/ directory for debugging with the MCP Inspector tool. These work with both pipx and uvx installations and are platform-independent.