This project contains an MCP server for Bronto.
It currently provides tools for models to access details on Bronto datasets, top-keys as well as event and statistical searches. When these tools are provided to an AI agent, they make it possible to answer questions such as
Can you please provide some log events from datasets in the ingestion collection, except for the ones related to garbage collection? The data should be between "2025-05-10 16:05:45" and "2025-05-10 16:25:05".
Check out this project, then create a virtual environment at its root. Finally install the requirements, e.g.
python3 -m venv env
env/bin/pip install -r requirements.txtThis MCP server is configured using environment variables:
BRONTO_API_KEY: a Bronto API keyBRONTO_API_ENDPOINT: a Bronto API endpoint, e.g. https://api.eu.staging.bronto.io
To run the mcp server from the root of this project, you can use the following command:
BRONTO_API_KEY=<API KEY HERE> \
BRONTO_API_ENDPOINT=https://api.eu.bronto.io \
PYTHONPATH=src/main/ \
env/bin/python src/main/brmcpserver/main.pyThis MCP server should work with any agent that supports MCP. However, it has only been tested with Claude Code.
Finally, in order to configure Claude Code so that it uses the Bronto MCP server, simply run
claude mcp add --transport http bronto http://localhost:8000Note: this will make the Bronto MCP server available to your current project/folder. If you wish to make the server
available globally, simply add --scope user to the command above. Details on how to manage MCP servers with
Claude Code can be found at https://docs.anthropic.com/en/docs/claude-code/mcp
Then launch Claude Code and run the /mcp command to check that the Bronto MCP server is available and that Claude Code
was able to connect to it.