Prometheux MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Prometheux MCP ServerWhat concepts are available in project customer-analytics?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Prometheux MCP Server
A Model Context Protocol (MCP) client that enables AI agents like Claude to interact with Prometheux knowledge graphs and reasoning capabilities.
For Users
What This Does
This package lets you use Claude Desktop to interact with your Prometheux projects:
List concepts in your projects
Run concepts to derive new knowledge
All through natural conversation with Claude
Prerequisites
Prometheux account with access to a deployed instance
Claude Desktop installed on your machine
Your authentication token from your Prometheux account settings
Installation
Option 1: Automated Install (Recommended)
The easiest way to install - download and run our installation script:
macOS/Linux:
curl -sSL https://raw.githubusercontent.com/prometheuxresearch/px-mcp-server/main/install.sh -o install.sh
chmod +x install.sh
./install.shWindows (PowerShell):
Invoke-WebRequest -Uri "https://raw.githubusercontent.com/prometheuxresearch/px-mcp-server/main/install.ps1" -OutFile "install.ps1"
.\install.ps1The script will:
✅ Install
pipx(if not already installed)✅ Install
prometheux-mcppackage✅ Prompt for your credentials (URL, token, username, organization)
✅ Automatically configure Claude Desktop
✅ Create backups of existing configuration
Then just restart Claude Desktop and you're ready!
Option 2: Manual Install Using pipx
If you prefer manual installation, use pipx to install the package in an isolated environment:
macOS:
brew install pipx
pipx ensurepath
pipx install prometheux-mcpWindows:
pip install pipx
pipx ensurepath
pipx install prometheux-mcpLinux:
pip install pipx
pipx ensurepath
pipx install prometheux-mcpConfiguration
Note: If you used the automated installation script (Option 1), configuration was done automatically. Skip to the "Using Prometheux with Claude" section below.
For manual installations (Option 2):
Get your credentials from your Prometheux account settings:
Server URL (e.g.,
https://api.prometheux.ai)Authentication token
Username
Organization
Configure Claude Desktop by editing the config file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Windows:%APPDATA%\Claude\claude_desktop_config.jsonConfiguration Example:
{ "mcpServers": { "prometheux": { "command": "/Users/YOUR_USERNAME/.local/bin/prometheux-mcp", "args": ["--url", "https://api.prometheux.ai"], "env": { "PROMETHEUX_TOKEN": "your_token_here", "PROMETHEUX_USERNAME": "your_username", "PROMETHEUX_ORGANIZATION": "your_org" } } } }Finding Your Path: Run this in your terminal to find the full path:
macOS/Linux:
which prometheux-mcpWindows:
where prometheux-mcp(in PowerShell or Command Prompt)
Common paths after pipx install:
macOS:
/Users/YOUR_USERNAME/.local/bin/prometheux-mcpWindows:
C:\\Users\\YOUR_USERNAME\\.local\\bin\\prometheux-mcp.exe(use double backslashes in JSON)Linux:
/home/YOUR_USERNAME/.local/bin/prometheux-mcp
Note: Username and organization are required for API routing through the gateway.
Custom URLs: For on-premise deployments or custom URLs, replace
https://api.prometheux.aiwith your own server URL.Restart Claude Desktop (quit completely with Cmd+Q, then reopen)
Usage
Once configured, just chat with Claude:
"What concepts are available in project customer-analytics?"
"Run the churn_prediction concept in project customer-analytics"
"Show me the high_value_customers from project sales-data with min_value of 1000"
Available Tools
Tool | Description |
| Lists all concepts in a project |
| Executes a concept to derive new knowledge |
Troubleshooting
"command not found" or "Server disconnected" errors:
macOS:
Find the full path:
which prometheux-mcpUse that full path in your config (usually
/Users/YOUR_USERNAME/.local/bin/prometheux-mcp)If still having issues, try pipx:
pipx install prometheux-mcpRestart Claude Desktop completely (Cmd+Q, then reopen)
Windows:
Find the full path:
where prometheux-mcp(in PowerShell or Command Prompt)Use that full path in your config with double backslashes (e.g.,
C:\\Users\\YOUR_USERNAME\\.local\\bin\\prometheux-mcp.exe)Restart Claude Desktop
"Connection refused" error:
Check that your Prometheux server URL is correct and accessible. Test with: curl [YOUR_URL]/mcp/info
"Authentication failed" error: Verify your token is correct in the config. Generate a new token from your Prometheux account settings if needed.
Check logs:
macOS:
~/Library/Logs/Claude/mcp-server-prometheux.logWindows:
%APPDATA%\Claude\logs\mcp-server-prometheux.log
Related MCP server: A2A MCP Server
Tool Reference
list_concepts
Lists all concepts available in a project.
Parameters:
Parameter | Type | Required | Default | Description |
| string | Yes | — | Project identifier |
| string | No |
|
|
Example response:
{
"concepts": [
{
"predicate_name": "customer",
"fields": {"id": "string", "name": "string"},
"column_count": 2,
"is_input": true,
"row_count": 1000,
"type": "postgresql",
"description": "Customer records"
}
],
"count": 1
}run_concept
Executes a concept to derive new knowledge through Vadalog reasoning.
Parameters:
Parameter | Type | Required | Default | Description |
| string | Yes | — | Project identifier |
| string | Yes | — | Concept to execute |
| object | No |
| Parameters for reasoning |
| string | No |
|
|
| boolean | No |
| Re-execute even if cached |
| boolean | No |
| Save results to database |
Example response:
{
"concept_name": "high_value_customers",
"message": "Concept executed successfully",
"evaluation_results": {
"resultSet": {
"high_value_customers": [["Alice", 5000], ["Bob", 3000]]
},
"columnNames": {
"high_value_customers": ["name", "total_value"]
}
},
"predicates_populated": ["high_value_customers"],
"total_records": 2
}For Maintainers
Releasing a New Version
# 1. Update version
echo "0.1.6" > version.txt
# 2. Build and publish to PyPI
python -m build
twine upload dist/*
# 3. Commit and tag
git add version.txt
git commit -m "Release version 0.1.6"
git push
git tag v0.1.6
git push origin v0.1.6Users will automatically get the new version when they run the installation script or pipx install prometheux-mcp.
Access to Prometheux Backend
The Prometheux backend is required to use this MCP client. To request access:
📧 Email: davben@prometheux.co.uk, teodoro.baldazzi@prometheux.co.uk, or support@prometheux.co.uk
🌐 Website: https://www.prometheux.ai
License
BSD 3-Clause License — see LICENSE file for details.
About Prometheux
Prometheux is an ontology native data engine that processes data anywhere it lives. Define ontologies once and unlock knowledge that spans databases, warehouses, and platforms—built on the Vadalog reasoning engine.
Key capabilities:
Connect: Query across Snowflake, Databricks, Neo4j, SQL, CSV, and more without ETL or vendor lock-in
Think: Replace 100+ lines of PySpark/SQL with simple declarative logic. Power graph analytics without GraphDBs
Explain: Full lineage & traceability with deterministic, repeatable results. Ground AI in structured, explainable context
Exponentially faster and simpler than traditional approaches. Learn more at prometheux.ai.
Support
For issues, questions, or access requests:
Homepage: https://www.prometheux.ai
Email: davben@prometheux.co.uk, teodoro.baldazzi@prometheux.co.uk, or support@prometheux.co.uk
Documentation: https://docs.prometheux.ai/mcp
Issues: GitHub Issues
Related Projects
Prometheux Chain — Python SDK for Prometheux
Vadalog Extension — JupyterLab extension for Vadalog
Vadalog Jupyter Kernel — Jupyter kernel for Vadalog
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