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Weights & Biases Server

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Enables querying W\&B Weave traces and creating W\&B Reports with text and visualizations through natural language.

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Описание

Enables querying W&B Weave traces and creating W&B Reports with text and visualizations through natural language.

README

A Model Context Protocol (MCP) server for querying Weights & Biases Weave traces. This server allows a MCP Client to:

  • query W&B Weave traces
  • write text and charts to W&B Reports

Available tools

wandb

  • query_wandb_gql_tool: Execute an arbitrary GraphQL query against wandb experiment tracking data including Projects, Runs, Artifacts, Sweeps, Reports, etc.

Weave

  • query_weave_traces_tool: Queries Weave traces with powerful filtering, sorting, and pagination options. Returns either complete trace data or just metadata to avoid overwhelming the LLM context window.

  • count_weave_traces_tool: Efficiently counts Weave traces matching given filters without returning the trace data. Returns both total trace count and root traces count to understand project scope before querying.

Saving Anaysis

  • create_wandb_report_tool: Creates a new W&B Report with markdown text and HTML-rendered visualizations. Provides a permanent, shareable document for saving analysis findings and generated charts.

Usage

Ensure you specify the W&B Entity and W&B Project to the LLM/MCP Client.

Example query for Claude Desktop:

how many openai.chat traces in the wandb-applied-ai-team/mcp-tests weave project? plot the most recent 5 traces over time and save to a report

Installation

git clone https://github.com/wandb/mcp-server.git
cd mcp-server && uv venv && source .venv/bin/activate
uv pip install -e .

Configuration

  1. Create a .env file in the root directory with your Weights & Biases API key:
WANDB_API_KEY=your_api_key_here

Running the Server

Run the server using:

uv run src/mcp_server/server.py

Client Setup

Claude Desktop

    "mcpServers": {
        "weights_and_biases": {
        "command": "uv",
        "args": [
            "--directory",
            "/ABSOLUTE/PATH/TO/PROJECT",
            "run",
            "src/mcp_server/server.py"
        ]
        }
    }

TODOs

  • Add W&B Models data
  • Convert to run with npx
  • Make more configurable: specify wandb URL
  • Work on reports plots prompt for consistent visualizations
  • Look into auth solutions

Troubleshooting

Error: spawn uv ENOENT

If you encounter an error like this when starting the MCP server:

Error: spawn uv ENOENT

This indicates that the uv package manager cannot be found. Fix this with these steps:

  1. Install uv using the official installation script:

    curl -LsSf https://astral.sh/uv/install.sh | sh
    
  2. If the error persists after installation, create a symlink to make uv available system-wide:

    sudo ln -s ~/.local/bin/uv /usr/local/bin/uv
    
  3. Restart your application or IDE after making these changes.

This ensures that the uv executable is accessible from standard system paths that are typically included in the PATH for all processes.

from github.com/riballes/mcp-server

Установка Weights & Biases Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/riballes/mcp-server

FAQ

Weights & Biases Server MCP бесплатный?

Да, Weights & Biases Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Weights & Biases Server?

Нет, Weights & Biases Server работает без API-ключей и переменных окружения.

Weights & Biases Server — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить Weights & Biases Server в Claude Desktop, Claude Code или Cursor?

Открой Weights & Biases Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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