Weights & Biases MCP Server
Provides tools for querying Weights & Biases Weave traces, executing GraphQL queries against wandb experiment tracking data, and creating W&B Reports with markdown and visualizations.
Click on "Deploy 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., "@Weights & Biases MCP Servercount weave traces in mcp-tests project and list top 5 by duration"
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.
Weights & Biases MCP Server
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.
Related MCP server: otel-mcp-server
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 reportInstallation
git clone https://github.com/wandb/mcp-server.git
cd mcp-server && uv venv && source .venv/bin/activate
uv pip install -e .Configuration
Create a
.envfile in the root directory with your Weights & Biases API key:
WANDB_API_KEY=your_api_key_hereRunning the Server
Run the server using:
uv run src/mcp_server/server.pyClient 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 ENOENTThis indicates that the uv package manager cannot be found. Fix this with these steps:
Install
uvusing the official installation script:curl -LsSf https://astral.sh/uv/install.sh | shIf the error persists after installation, create a symlink to make
uvavailable system-wide:sudo ln -s ~/.local/bin/uv /usr/local/bin/uvRestart 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.
This server cannot be deployed
Maintenance
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