Watsonx

Name: Watsonx
Author: ExpertVagabond

by ExpertVagabondversion 1.0.1i★ –iRuns on your computer

Registry nameio.github.ExpertVagabond/watsonx

Install

Overview

Description from the maker (original English)

IBM watsonx.ai MCP server for Claude integration

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "watsonx": {
      "command": "npx",
      "args": [
        "-y",
        "watsonx-mcp-server"
      ]
    }
  }
}

Run this in your terminal

claude mcp add watsonx -- npx -y watsonx-mcp-server

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "watsonx": {
      "command": "npx",
      "args": [
        "-y",
        "watsonx-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "watsonx": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "watsonx-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account ExpertVagabond, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 18431 servers in this category
Published to the registry more recently than 2% of the other 18431 servers in this category
Basic checks equal to or better than 100% of the other 18431 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Watsonx safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Tethered Trust

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago

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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 3 days ago

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Tethered Trust

by tetheredtrust.com

Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.

Runs in the cloudUpdated today

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

watsonx MCP Server

MCP server for IBM watsonx.ai integration with Claude Code. Enables Claude to delegate tasks to IBM's foundation models (Granite, Llama, Mistral, etc.).

Features

Text Generation - Generate text using watsonx.ai foundation models
Chat - Have conversations with watsonx.ai chat models
Embeddings - Generate text embeddings
Model Listing - List all available foundation models

Available Tools

Tool	Description
`watsonx_generate`	Generate text using watsonx.ai models
`watsonx_chat`	Chat with watsonx.ai models
`watsonx_embeddings`	Generate text embeddings
`watsonx_list_models`	List available models

Setup

1. Install Dependencies

cd ~/watsonx-mcp-server

npm install

2. Configure Environment

Set these environment variables:

WATSONX_API_KEY=your-ibm-cloud-api-key

WATSONX_URL=https://us-south.ml.cloud.ibm.com WATSONX_SPACE_ID=your-deployment-space-id # Recommended: deployment space WATSONX_PROJECT_ID=your-project-id # Alternative: project ID

Note: Either WATSONX_SPACE_ID or WATSONX_PROJECT_ID is required for text generation, embeddings, and chat. Deployment spaces are recommended as they have Watson Machine Learning (WML) pre-configured.

3. Add to Claude Code

The MCP server is already configured in ~/.claude.json:

"mcpServers": { "watsonx": { "type": "stdio", "command": "node", "args": ["/Users/matthewkarsten/watsonx-mcp-server/index.js"], "env": { "WATSONX_API_KEY": "your-api-key", "WATSONX_URL": "https://us-south.ml.cloud.ibm.com", "WATSONX_SPACE_ID": "your-deployment-space-id" } } } }

Usage

Once configured, Claude can use watsonx.ai tools:

User: Use watsonx to generate a haiku about coding

Claude: [Uses watsonx_generate tool] Result: Code flows like water Bugs arise, then disappear Programs come alive

Available Models

Some notable models available:

ibm/granite-3-3-8b-instruct - IBM Granite 3.3 8B (recommended)
ibm/granite-13b-chat-v2 - IBM Granite chat model
ibm/granite-3-8b-instruct - Granite 3 instruct model
meta-llama/llama-3-70b-instruct - Meta's Llama 3 70B
mistralai/mistral-large - Mistral AI large model
ibm/slate-125m-english-rtrvr-v2 - Embedding model

Use watsonx_list_models to see all available models.

Architecture

Claude Code (Opus 4.5)

│ └──▶ watsonx MCP Server │ └──▶ IBM watsonx.ai API │ ├── Granite Models ├── Llama Models ├── Mistral Models └── Embedding Models

Two-Agent System

This enables a two-agent architecture where:

Claude (Opus 4.5) - Primary reasoning agent, handles complex tasks
watsonx.ai - Secondary agent for specific workloads

Claude can delegate tasks to watsonx.ai when:

IBM-specific model capabilities are needed
Running batch inference on enterprise data
Using specialized Granite models
Generating embeddings for RAG pipelines

IBM Cloud Resources

This MCP server uses:

Service: watsonx.ai Studio (data-science-experience)
Plan: Lite (free tier)
Region: us-south

Create your own watsonx.ai project and deployment space in IBM Cloud.

Integration with IBM Z MCP Server

This watsonx MCP server works alongside the IBM Z MCP server:

Claude Code (Opus 4.5)

│ ├──▶ watsonx MCP Server │ └── Text generation, embeddings, chat │ └──▶ ibmz MCP Server └── Key Protect HSM, z/OS Connect

Demo scripts in the ibmz-mcp-server:

demo-full-stack.js - Full 5-service pipeline
demo-rag.js - RAG with watsonx embeddings + Granite

Document Analyzer

The document analyzer (document-analyzer.js) provides powerful tools for analyzing your external drive data using watsonx.ai:

Commands

# View document catalog (9,168 documents)

node document-analyzer.js catalog

Summarize a document

node document-analyzer.js summarize 1002519.txt

Analyze document type, topics, entities

node document-analyzer.js analyze 1002519.txt

Ask questions about a document

node document-analyzer.js question 1002519.txt 'What AWS credentials are needed?'

Generate embeddings for documents

node document-analyzer.js embed

Semantic search across documents

node document-analyzer.js search 'IBM Cloud infrastructure'

Features

Summarization: Generate concise summaries of any document
Analysis: Extract document type, topics, entities, and sentiment
Q&A: Ask natural language questions about document content
Embeddings: Generate 768-dimensional vectors for semantic search
Semantic Search: Find similar documents using vector similarity

Demo

Run the full demo:

./demo-external-drive.sh

Embedding Index & RAG

The embedding-index.js tool provides semantic search and RAG (Retrieval Augmented Generation):

# Build an embedding index (50 documents)

node embedding-index.js build 50

Semantic search

node embedding-index.js search 'cloud infrastructure'

RAG query - retrieves relevant docs and generates answer

node embedding-index.js rag 'How do I set up AWS for Satellite?'

Show index statistics

node embedding-index.js stats

Batch Processor

The batch-processor.js tool processes multiple documents at once:

# Classify documents into categories

node batch-processor.js classify 20

Extract topics from documents

node batch-processor.js topics 15

Generate one-line summaries

node batch-processor.js summarize 10

Full analysis (classify + topics + summary)

node batch-processor.js full 10

Categories: technical, business, creative, personal, code, legal, marketing, educational, other

Files

index.js - MCP server implementation
document-analyzer.js - Document analysis CLI tool
embedding-index.js - Embedding index and RAG tool
batch-processor.js - Batch document processor
demo-external-drive.sh - Demo script
package.json - Dependencies
README.md - This file

Author

Matthew Karsten

License

MIT

Watsonx

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Tethered Trust

README from the maker

watsonx MCP Server

Features

Available Tools

Setup

1. Install Dependencies

2. Configure Environment

3. Add to Claude Code

Usage

Available Models

Architecture

Two-Agent System

IBM Cloud Resources

Integration with IBM Z MCP Server

Document Analyzer

Commands

Summarize a document

Analyze document type, topics, entities

Ask questions about a document

Generate embeddings for documents

Semantic search across documents

Features

Demo

Embedding Index & RAG

Semantic search

RAG query - retrieves relevant docs and generates answer

Show index statistics

Batch Processor

Extract topics from documents

Generate one-line summaries

Full analysis (classify + topics + summary)

Files

Author

License