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IBM watsonx.ai Granite

IBM watsonx.ai Granite

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three.wsAI & Agents255Updated today

About IBM watsonx.ai Granite

IBM watsonx.ai Granite is an MCP server that calls IBM Granite and other watsonx.ai models through the REST API, using the user's own IBM Cloud credentials. It is intended for developers who want watsonx.ai inside MCP clients, and it handles IAM token exchange and caching itself. The project is community-built and not affiliated with IBM.

Key features

  1. 01Chat completion and raw text generation
  2. 02Text embeddings, up to 1000 inputs per call
  3. 03Token counting and optional tokenization
  4. 04Zero-shot time-series forecasting with Granite TimeSeries
  5. 05Lists foundation models available to the account
  6. 06IAM token cached in-process and refreshed before expiry

Use cases

  1. 01Generating text with Granite models from Claude Code or Cursor
  2. 02Creating embedding vectors for document retrieval
  3. 03Forecasting time-series data without task-specific training

MCP support

The project runs as an MCP server and exposes watsonx_chat, watsonx_generate, watsonx_embed, watsonx_tokenize, watsonx_forecast and watsonx_list_models tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"nirholas-ibm-watsonx": {
"command": "npx",
"args": [
"-y",
"@three-ws/ibm-watsonx-mcp"
],
"env": {
"WATSONX_API_KEY": "<WATSONX_API_KEY>",
"WATSONX_PROJECT_ID": "<WATSONX_PROJECT_ID>",
"WATSONX_SPACE_ID": "<WATSONX_SPACE_ID>",
"WATSONX_URL": "<WATSONX_URL>",
"WATSONX_MODEL_ID": "<WATSONX_MODEL_ID>",
"WATSONX_EMBED_MODEL_ID": "<WATSONX_EMBED_MODEL_ID>",
"WATSONX_API_VERSION": "<WATSONX_API_VERSION>"
}
}
}
}
Run commandnpx -y @three-ws/ibm-watsonx-mcp
Environment variables to set
WATSONX_API_KEYSecretIBM Cloud API key (create one at https://cloud.ibm.com/iam/apikeys).
WATSONX_PROJECT_IDwatsonx.ai project id (Project → Manage → General → Project ID). Provide this or WATSONX_SPACE_ID.
WATSONX_SPACE_IDwatsonx.ai deployment space id. Alternative to WATSONX_PROJECT_ID.
WATSONX_URLRegional inference host. Defaults to https://us-south.ml.cloud.ibm.com.
WATSONX_MODEL_IDDefault chat/generation model id. Defaults to ibm/granite-3-8b-instruct.
WATSONX_EMBED_MODEL_IDDefault embedding model id. Defaults to ibm/granite-embedding-278m-multilingual.
WATSONX_API_VERSIONwatsonx.ai REST API version date. Defaults to 2024-05-31.

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@three-ws/ibm-watsonx-mcp0.2.2

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

three.ws

@three-ws/ibm-watsonx-mcp

MCP server for IBM watsonx.ai — chat, generation, embeddings, tokenization, forecasting, and model discovery, on your own IBM Cloud account.

npm downloads license node MCP Registry three.ws

Install · Quick start · Tools · Requirements · three.ws


A Model Context Protocol server that exposes IBM watsonx.ai — IBM Granite foundation models and anything else in your account — to MCP clients such as Claude Desktop, Claude Code, and Cursor. It talks directly to the watsonx.ai as-a-Service REST API with your own IBM Cloud credentials: it mints an IAM bearer token from your API key, caches it until just before expiry, and scopes every call to your project. No intermediary backend, no telemetry, no mock data.

Community-built and not affiliated with IBM. Registry name: io.github.nirholas/ibm-watsonx.

Install

npm install @three-ws/ibm-watsonx-mcp

Run it directly with npx (no install needed):

WATSONX_API_KEY=... WATSONX_PROJECT_ID=... npx @three-ws/ibm-watsonx-mcp

Or install globally to get the ibm-watsonx-mcp binary on your PATH:

npm install -g @three-ws/ibm-watsonx-mcp

Quick start

With Claude Code, one command:

claude mcp add ibm-watsonx -e WATSONX_API_KEY=... -e WATSONX_PROJECT_ID=... -- npx -y @three-ws/ibm-watsonx-mcp

Or add the server to your MCP client config (claude_desktop_config.json, Cursor's mcp.json):

{
	"mcpServers": {
		"ibm-watsonx": {
			"command": "npx",
			"args": ["-y", "@three-ws/ibm-watsonx-mcp"],
			"env": {
				"WATSONX_API_KEY": "your-ibm-cloud-api-key",
				"WATSONX_PROJECT_ID": "your-watsonx-project-id"
			}
		}
	}
}

Restart the client and the six tools below appear. Inspect the surface manually with the MCP Inspector:

npx -y @modelcontextprotocol/inspector npx @three-ws/ibm-watsonx-mcp

Tools

ToolWhat it does
watsonx_chatChat completion from a list of role/content messages. Returns the reply plus token usage.
watsonx_generateRaw prompt completion with decoding control (greedy/sample, stop sequences).
watsonx_embedEmbedding vectors for one or more texts (up to 1000). One vector per input plus dimensionality.
watsonx_tokenizeToken count (and optionally the tokens) for a text against a model tokenizer.
watsonx_forecastZero-shot time-series forecasting with an IBM Granite TimeSeries (TinyTimeMixer) model.
watsonx_list_modelsList the foundation models available to your account and region, optionally filtered.

Every tool is a read-only model-inference call — nothing in your environment or IBM account is modified — and declares MCP tool annotations (readOnlyHint, openWorldHint, idempotentHint) so clients can reason about side effects.

Input parameters

watsonx_chat — messages (required: array of { role, content }, roles system/user/assistant), model, max_tokens (1–4096), temperature (0–2), top_p (0–1).

watsonx_generate — input (required), model, max_new_tokens (1–4096), temperature (0–2), decoding_method (greedy/sample), stop_sequences.

watsonx_embed — inputs (required: 1–1000 texts), model.

watsonx_tokenize — input (required), model, return_tokens (boolean).

watsonx_forecast — timestamps (required: ISO-8601, uniform cadence, oldest first), values (required: numeric, same length), freq (required: pandas cadence, e.g. 1h, 15min, 1D), model, target_column, prediction_length (1–96).

watsonx_list_models — filter (e.g. function_text_generation, function_embedding), limit (1–200, default 100).

Example calls
// watsonx_chat
{ "messages": [{ "role": "user", "content": "Explain MCP in one sentence." }] }

// watsonx_generate
{ "input": "Write a haiku about Kubernetes.", "decoding_method": "sample", "temperature": 0.7, "max_new_tokens": 60 }

// watsonx_embed
{ "inputs": ["lakehouse", "data warehouse"] }

// watsonx_forecast
{ "timestamps": ["2025-01-01T00:00:00Z", "2025-01-01T01:00:00Z"], "values": [1200, 1180], "freq": "1h", "prediction_length": 24 }

// watsonx_list_models
{ "filter": "function_embedding" }

How auth works

WATSONX_API_KEY is exchanged for a short-lived IAM bearer token at https://iam.cloud.ibm.com/identity/token (grant_type=urn:ibm:params:oauth:grant-type:apikey). The token is cached in-process and refreshed about five minutes before it expires. Your API key never leaves your machine except in that single IAM exchange.

Requirements

  • Node.js >= 20.
  • An IBM Cloud account with watsonx.ai provisioned — sign up (free tier available).
  • An IBM Cloud API key — create one at https://cloud.ibm.com/iam/apikeys.
  • Your watsonx.ai project id — open the project → Manage → General → Project ID (or a deployment space id).
Environment variables
VariableRequiredDefault
WATSONX_API_KEYyes—
WATSONX_PROJECT_IDyes (or WATSONX_SPACE_ID)—
WATSONX_SPACE_IDalternative to WATSONX_PROJECT_ID—
WATSONX_URLnohttps://us-south.ml.cloud.ibm.com
WATSONX_MODEL_IDnoibm/granite-3-8b-instruct
WATSONX_EMBED_MODEL_IDnoibm/granite-embedding-278m-multilingual
WATSONX_FORECAST_MODELnoibm/granite-ttm-512-96-r2
WATSONX_API_VERSIONno2024-05-31
WATSONX_TS_API_VERSIONno2025-02-11 (time-series API date)
WATSONX_TIMEOUT_MSno60000
WATSONX_IAM_URLnohttps://iam.cloud.ibm.com/identity/token

Regional hosts: us-south, eu-de, eu-gb, jp-tok, au-syd, ca-tor — e.g. https://eu-de.ml.cloud.ibm.com.

Related

  • @three-ws/ibm-x402-mcp — the same IBM Granite tools as pay-per-use x402 endpoints (USDC on Solana), so callers need no IBM account of their own.

Links


Part of the three.ws SDK suite — 3D AI agents, on-chain identity, and agent payments.
Website · Changelog · GitHub

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