Weka

iamademar2stars

MCP server for WEKA machine learning. Train, evaluate, and run ML models from Claude, ChatGPT, and any MCP client. Java REST API + TypeScript MCP server, deployable to Azure Container Apps.

Cloud Infrastructure Data Science Ml

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Weka

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: GPL-3.0
Last checked: 2026-10-27

Stars: 2
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Weka?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Weka need an API key?

No required environment variable is listed on this record.

What transport does Weka use?

Weka runs locally over stdio.

When was Weka last checked?

Last checked 2026-10-27. MCP server for WEKA machine learning. Train, evaluate, and run ML models from Claude, ChatGPT, and any MCP client. Java REST API + TypeScript MCP server, deployable to Azure Container Apps.

From the publisher

Documentation

WEKA-MCP

What is this? It's basically the WEKA the machine-learning library that allows you to upload data, train/evaluate classifiers, cluster, mine association rules, run diagnostics but served by your favor LLM through 46 typed Model Context Protocol tools.

Here’s the high-level architecture:

  MCP client ──▶ weka-mcp ──▶ weka-api ──▶ WEKA library
               (:3000 /mcp)  (:7070 REST)   (real ML)
                  or stdio

weka-api — Java 17 / Javalin REST service wrapping WEKA 3.9.6. Does the real ML. Persists models to /app/models and datasets to /app/data. Listens on 7070.
weka-mcp — TypeScript/Node MCP server. A thin, typed forwarder — no ML logic; it translates each MCP tool call into a weka-api REST call. Supports HTTP (POST /mcp) and stdio transports. Finds weka-api via WEKA_API_URL.

Run it locally

Prerequisites: Docker + Docker Compose v2. (For stdio dev outside Docker: Node ≥ 20.)

bin/setup     # build + start; auto-selects free host ports, then waits for health

bin/setup is the one-command install: it probes for free host ports (starting at 3001 for weka-mcp and 7070 for weka-api), records them in a generated .env, runs docker compose up --build -d, and waits until weka-mcp reports healthy. It prints the endpoints when done. The plain docker compose up --build -d still works if you'd rather manage ports yourself (defaults / .env).

weka-api starts first; weka-mcp waits until weka-api reports healthy (depends_on + healthcheck). Both services publish a host port locally; the internal mcp→api wiring stays on the service name (weka-api:7070), mirroring the cloud shape where weka-api is internal-only.

Check it's up (bin/setup prints the exact ports it chose):

curl -s localhost:3001/healthz
# {"ok":true,"wekaApiUrl":"http://weka-api:7070"}

Tear down:

bin/remove                # down -v (wipes model/data volumes), removes images, frees the ports
# or, manually:
docker compose down       # stop containers, keep model/data volumes
docker compose down -v    # also wipe the weka-models + weka-data volumes

Connecting an MCP client

HTTP transport (the deployed shape)

Point any MCP-over-HTTP client at http://localhost:3001/mcp. Locally the auth check is skipped. The cloud deployment can run open (no header — so ChatGPT / claude.ai / Claude Desktop connect with zero setup) or secured (requires an X-Internal-Auth: <secret> header); see infrastructure/README.md → Connect a client.

stdio transport (Claude Desktop / Claude Code)

Desktop clients speak MCP over stdio. Build once, then run dist/index.js with WEKA_API_URL pointed at a running weka-api:

cd weka-mcp && npm ci && npm run build

Claude Code:

claude mcp add weka \
  --env WEKA_API_URL=http://localhost:7070 \
  -- node "/ABSOLUTE/PATH/TO/weka-mcp-core/weka-mcp/dist/index.js"

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "weka": {
      "command": "node",
      "args": ["/ABSOLUTE/PATH/TO/weka-mcp-core/weka-mcp/dist/index.js"],
      "env": { "WEKA_API_URL": "http://localhost:7070" }
    }
  }
}

stdio needs weka-api reachable at WEKA_API_URL. The compose stack does not publish weka-api to the host; for stdio dev either run weka-api directly (cd weka-api && mvn -q package -DskipTests && PORT=7070 java -jar target/weka-api-*-shaded.jar) or temporarily add ports: ["7070:7070"] to the weka-api service in compose.yaml.

Environment variables

weka-api (read in weka-api/src/main/java/com/wekaapi/config/Config.java):

Variable	Default	Purpose
`PORT`	`7070`	HTTP port Javalin binds
`MODELS_DIR`	`/app/models`	serialized `.model` files
`DATA_DIR`	`/app/data`	uploaded ARFF/CSV datasets
`MAX_UPLOAD_MB`	`100`	upload size cap (MB)
`LOG_LEVEL`	`INFO`	Logback root level
`JAVA_TOOL_OPTIONS`	(unset)	JVM flags; compose sets `-XX:MaxRAMPercentage=75.0` under the container cap

weka-mcp (read in weka-mcp/src/config.ts and client.ts):

Variable	Default	Purpose
`WEKA_API_URL`	`http://localhost:7070`	base URL of weka-api (compose: `http://weka-api:7070`)
`MCP_HTTP_PORT`	`3000`	port the HTTP transport listens on (`POST /mcp`)
`WEKA_API_TIMEOUT_MS`	`210000`	per-request timeout to weka-api (kept < ~240s Envoy ceiling)
`INTERNAL_AUTH_SHARED_SECRET`	(unset)	if set, `POST /mcp` requires header `X-Internal-Auth: <secret>`; unset ⇒ check skipped

MCP_HOST_PORT (default 3001) is a compose-only convenience that sets the host port published for weka-mcp; the container still listens on MCP_HTTP_PORT (3000). See .env.example.

The tool surface (46 tools, all `weka_`-prefixed)

Group	Tools
Health / discovery	`weka_health`, `weka_list_algorithms`, `weka_list_clusterers`, `weka_list_associators`, `weka_list_as_evaluators`, `weka_list_as_searches`, `weka_list_filters`, `weka_filter_metadata`
Datasets	`weka_list_datasets`, `weka_get_dataset`, `weka_upload_dataset`, `weka_delete_dataset`
EDA	`weka_attribute_stats`, `weka_dataset_summary`, `weka_histogram`, `weka_scatter`, `weka_scatter_matrix`
Transform	`weka_transform`, `weka_transform_preview`, `weka_attribute_selection`
Train / predict / evaluate	`weka_train`, `weka_train_search`, `weka_train_update`, `weka_predict`, `weka_predict_dataset`, `weka_evaluate`, `weka_experiment`, `weka_learning_curve`
Models	`weka_list_models`, `weka_get_model`, `weka_delete_model`, `weka_model_tree`, `weka_model_graph`, `weka_download_model`, `weka_import_model`
Clustering	`weka_cluster_train`, `weka_cluster_assign`, `weka_cluster_evaluate`
Association	`weka_associate`
Diagnostics	`weka_diag_errors`, `weka_diag_threshold_curve`, `weka_diag_margin_curve`, `weka_diag_cost_curve`, `weka_diag_calibration`, `weka_diag_residuals`, `weka_diag_pr_curve`

Run cd weka-mcp && npm run smoke to assert all 46 register with descriptions (no API needed). The per-service READMEs — weka-mcp/README.md and WEKA-ORIGINAL-README.md (the REST API contract) — go deeper on individual tools/endpoints.

Deploy to Azure

Container Apps + Bicep, as infra-as-code, lives in infrastructure/: weka-api gets internal-only ingress (never public); weka-mcp gets public ingress — either open for a zero-setup public demo or secured behind the X-Internal-Auth header. Cost is bounded by scale-to-zero + a hard maxReplicas cap + a monthly budget alert, and an Azure Files share backs the models/data volumes. See infrastructure/README.md for deploy steps and how to connect ChatGPT / Claude.

Weka

iamademar2stars

MCP server for WEKA machine learning. Train, evaluate, and run ML models from Claude, ChatGPT, and any MCP client. Java REST API + TypeScript MCP server, deployable to Azure Container Apps.

Cloud Infrastructure Data Science Ml

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Weka

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: GPL-3.0
Last checked: 2026-10-27

Stars: 2
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Weka?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Weka need an API key?

No required environment variable is listed on this record.

What transport does Weka use?

Weka runs locally over stdio.

When was Weka last checked?

From the publisher

Documentation

WEKA-MCP

Here’s the high-level architecture:

  MCP client ──▶ weka-mcp ──▶ weka-api ──▶ WEKA library
               (:3000 /mcp)  (:7070 REST)   (real ML)
                  or stdio

weka-api — Java 17 / Javalin REST service wrapping WEKA 3.9.6. Does the real ML. Persists models to /app/models and datasets to /app/data. Listens on 7070.
weka-mcp — TypeScript/Node MCP server. A thin, typed forwarder — no ML logic; it translates each MCP tool call into a weka-api REST call. Supports HTTP (POST /mcp) and stdio transports. Finds weka-api via WEKA_API_URL.

Run it locally

Prerequisites: Docker + Docker Compose v2. (For stdio dev outside Docker: Node ≥ 20.)

bin/setup     # build + start; auto-selects free host ports, then waits for health

Check it's up (bin/setup prints the exact ports it chose):

curl -s localhost:3001/healthz
# {"ok":true,"wekaApiUrl":"http://weka-api:7070"}

Tear down:

bin/remove                # down -v (wipes model/data volumes), removes images, frees the ports
# or, manually:
docker compose down       # stop containers, keep model/data volumes
docker compose down -v    # also wipe the weka-models + weka-data volumes

Connecting an MCP client

HTTP transport (the deployed shape)

stdio transport (Claude Desktop / Claude Code)

Desktop clients speak MCP over stdio. Build once, then run dist/index.js with WEKA_API_URL pointed at a running weka-api:

cd weka-mcp && npm ci && npm run build

Claude Code:

claude mcp add weka \
  --env WEKA_API_URL=http://localhost:7070 \
  -- node "/ABSOLUTE/PATH/TO/weka-mcp-core/weka-mcp/dist/index.js"

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "weka": {
      "command": "node",
      "args": ["/ABSOLUTE/PATH/TO/weka-mcp-core/weka-mcp/dist/index.js"],
      "env": { "WEKA_API_URL": "http://localhost:7070" }
    }
  }
}

stdio needs weka-api reachable at WEKA_API_URL. The compose stack does not publish weka-api to the host; for stdio dev either run weka-api directly (cd weka-api && mvn -q package -DskipTests && PORT=7070 java -jar target/weka-api-*-shaded.jar) or temporarily add ports: ["7070:7070"] to the weka-api service in compose.yaml.

Environment variables

weka-api (read in weka-api/src/main/java/com/wekaapi/config/Config.java):

Variable	Default	Purpose
`PORT`	`7070`	HTTP port Javalin binds
`MODELS_DIR`	`/app/models`	serialized `.model` files
`DATA_DIR`	`/app/data`	uploaded ARFF/CSV datasets
`MAX_UPLOAD_MB`	`100`	upload size cap (MB)
`LOG_LEVEL`	`INFO`	Logback root level
`JAVA_TOOL_OPTIONS`	(unset)	JVM flags; compose sets `-XX:MaxRAMPercentage=75.0` under the container cap

weka-mcp (read in weka-mcp/src/config.ts and client.ts):

Variable	Default	Purpose
`WEKA_API_URL`	`http://localhost:7070`	base URL of weka-api (compose: `http://weka-api:7070`)
`MCP_HTTP_PORT`	`3000`	port the HTTP transport listens on (`POST /mcp`)
`WEKA_API_TIMEOUT_MS`	`210000`	per-request timeout to weka-api (kept < ~240s Envoy ceiling)
`INTERNAL_AUTH_SHARED_SECRET`	(unset)	if set, `POST /mcp` requires header `X-Internal-Auth: <secret>`; unset ⇒ check skipped

MCP_HOST_PORT (default 3001) is a compose-only convenience that sets the host port published for weka-mcp; the container still listens on MCP_HTTP_PORT (3000). See .env.example.

The tool surface (46 tools, all `weka_`-prefixed)

Group	Tools
Health / discovery	`weka_health`, `weka_list_algorithms`, `weka_list_clusterers`, `weka_list_associators`, `weka_list_as_evaluators`, `weka_list_as_searches`, `weka_list_filters`, `weka_filter_metadata`
Datasets	`weka_list_datasets`, `weka_get_dataset`, `weka_upload_dataset`, `weka_delete_dataset`
EDA	`weka_attribute_stats`, `weka_dataset_summary`, `weka_histogram`, `weka_scatter`, `weka_scatter_matrix`
Transform	`weka_transform`, `weka_transform_preview`, `weka_attribute_selection`
Train / predict / evaluate	`weka_train`, `weka_train_search`, `weka_train_update`, `weka_predict`, `weka_predict_dataset`, `weka_evaluate`, `weka_experiment`, `weka_learning_curve`
Models	`weka_list_models`, `weka_get_model`, `weka_delete_model`, `weka_model_tree`, `weka_model_graph`, `weka_download_model`, `weka_import_model`
Clustering	`weka_cluster_train`, `weka_cluster_assign`, `weka_cluster_evaluate`
Association	`weka_associate`
Diagnostics	`weka_diag_errors`, `weka_diag_threshold_curve`, `weka_diag_margin_curve`, `weka_diag_cost_curve`, `weka_diag_calibration`, `weka_diag_residuals`, `weka_diag_pr_curve`

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Weka?

Does Weka need an API key?

What transport does Weka use?

When was Weka last checked?

Documentation

WEKA-MCP

Run it locally

Connecting an MCP client

HTTP transport (the deployed shape)

stdio transport (Claude Desktop / Claude Code)

Environment variables

The tool surface (46 tools, all weka_-prefixed)

Deploy to Azure

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Weka?

Does Weka need an API key?

What transport does Weka use?

When was Weka last checked?

Documentation

WEKA-MCP

Run it locally

Connecting an MCP client

HTTP transport (the deployed shape)

stdio transport (Claude Desktop / Claude Code)

Environment variables

The tool surface (46 tools, all weka_-prefixed)

Deploy to Azure

The tool surface (46 tools, all `weka_`-prefixed)

The tool surface (46 tools, all `weka_`-prefixed)