> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bronto.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Local MCP Server
> Run the open-source Bronto MCP server locally with Python and connect Claude Code or any MCP agent to your datasets, API keys, and log search tools.
The local MCP server is open source and available on
[GitHub](https://github.com/brontoio/bronto-mcp-server). If you prefer not
to run infrastructure locally, see the [Hosted MCP Server](./hosted-mcp)
instead.
## Overview
The Bronto MCP server is a local Python server that exposes Bronto's dataset and log search capabilities to any MCP-compatible AI agent. Once running, it gives agents the tools to answer questions against your live log data, for example:
> *"Can you 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."*
The server has been tested with Claude Code and should work with any agent that supports the MCP protocol.
***
## Prerequisites
* Python 3 installed on your machine
* A Bronto API key (see [API Keys](../Account-Management/API-Keys))
* Your Bronto API endpoint URL
***
## Installation
Check out the project from GitHub:
```bash theme={"dark"}
git clone https://github.com/brontoio/bronto-mcp-server.git
cd bronto-mcp-server
```
Create a Python virtual environment at the root of the project:
```bash theme={"dark"}
python3 -m venv env
```
Install the required packages into the virtual environment:
```bash theme={"dark"}
env/bin/pip install -r requirements.txt
```
***
## Configuration
The MCP server is configured using environment variables. Set both before starting the server.
| Variable | Description | Example |
| --------------------- | --------------------------------------- | -------------------------- |
| `BRONTO_API_KEY` | A valid Bronto API key | `68ba7ae3-...` |
| `BRONTO_API_ENDPOINT` | The Bronto API endpoint for your region | `https://api.eu.bronto.io` |
| Region | API Endpoint |
| ------ | -------------------------- |
| US | `https://api.us.bronto.io` |
| EU | `https://api.eu.bronto.io` |
***
## Starting the Server
Run the following command from the root of the project, substituting your API key and endpoint:
```bash theme={"dark"}
BRONTO_API_KEY= \
BRONTO_API_ENDPOINT=https://api.eu.bronto.io \
PYTHONPATH=src/main/ \
env/bin/python src/main/brmcpserver/main.py
```
The server starts on `http://localhost:8000` by default.
Keep your terminal session open while using the MCP server. Closing it will
stop the server and disconnect any connected agents.
***
## Connecting Claude Code
Once the server is running, register it with Claude Code using the following command:
```bash theme={"dark"}
claude mcp add --transport http bronto http://localhost:8000
```
This makes the Bronto MCP server available for your current project folder. To make it available globally across all projects, add the `--scope user` flag:
```bash theme={"dark"}
claude mcp add --transport http bronto http://localhost:8000 --scope user
```
Full documentation on managing MCP servers in Claude Code is available at
[docs.anthropic.com](https://docs.anthropic.com/en/docs/claude-code/mcp).
### Verify the connection
Launch Claude Code and run the `/mcp` command to confirm the Bronto MCP server is available and connected:
```
/mcp
──────────────────────────────────────
Manage MCP servers
1 servers Local MCPs
❯ bronto · ✓ connected
```
***
## Capabilities
Once connected, the server exposes the following tools to your AI agent.
| Tool | Description | When to use |
| ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `get_datasets` | Fetches all datasets in your Bronto account, including name, collection, log ID, and tags. Tags such as `description`, `service`, `team`, and `environment` are especially useful for understanding dataset contents. | When you need to discover what data sources are available, or find datasets by owner or environment. |
| `get_datasets_by_name` | Fetches a specific dataset by its exact name and collection name. A dataset is uniquely identified by the combination of both. | When you already know the dataset and collection name and need its log ID or tag metadata. |
| `get_keys` | Returns all field names present in a specific dataset, identified by its log ID. | To inspect a single dataset's schema before querying or filtering it. |
| `get_all_datasets_keys` | Returns a map of dataset IDs to their field names across all datasets. | To identify which datasets contain a particular field, or to determine the exact field name from a description. |
| `get_key_values` | Returns the available values for a specific field in a specific dataset. | To discover valid field values and build precise filters before running a search. |
| `search_logs` | Searches raw log events across one or more datasets over a time range. Supports SQL-style `WHERE` filters, multiple dataset IDs, and returns full log events including the `@raw` field. | Event-level investigations where you need to inspect individual log entries — for example, finding errors or warnings in a specific service. |
***
## Frequently Asked Questions
**Which AI agents are supported?**
The server implements the MCP protocol and should work with any MCP-compatible agent. It has been tested with Claude Code.
**Can I make the server available across all my projects?**
Yes. Add `--scope user` when registering the server with Claude Code and it will be available globally rather than only for the current project folder.
**Where do I find my API key?**
API keys can be created and managed in **Settings → API Keys** in the Bronto UI. See [API Keys](../Account-Management/API-Keys) for details.
**What is the difference between the local server and the hosted MCP server?**
The local server runs on your machine and requires Python, a virtual environment, and a running terminal session. The [hosted MCP server](./hosted-mcp) is managed by Bronto — there is nothing to install or run locally. For most teams the hosted option is simpler; the local server is useful if you need to run in an air-gapped environment or want to inspect or modify the server code directly.