Axiom MCP Server

• Hosted setup (Recommended)
• Local setup

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Current capabilities

• getDatasetSchema: Get dataset schema
• getMonitors: List monitoring configurations
• getMonitorsHistory: Get monitor execution history
• getSavedQueries: Retrieve saved APL queries
• listDatasets: List available Axiom datasets
• queryApl: Execute APL queries against Axiom datasets

• correlate-events-across-datasets: Find patterns and correlations between events across multiple datasets
• data-quality-investigation: Investigate data quality issues including missing data, inconsistencies, and collection problems
• detect-anomalies-in-events: Generic anomaly detection using statistical analysis and pattern recognition across any dataset
• establish-performance-baseline: Establish performance baselines for a dataset to enable effective monitoring and anomaly detection
• explore-unknown-dataset: Exploration of an unknown dataset to understand its structure, content, and potential use cases
• monitor-health-analysis: Comprehensive analysis of monitor health, alert patterns, and effectiveness

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Prerequisites

• Create an Axiom account.
• Create a dataset in Axiom where you send your data.

• Set up an AI agent that supports MCP. For example, install the Claude desktop app.

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Hosted setup

• Name: Axiom
• Server URL: https://mcp.axiom.co/mcp

• Claude desktop app
• Cursor

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Local setup

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Install

go install github.com/axiomhq/axiom-mcp@latest

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Create API token

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Configure

• Use a config file
• Use environment variables

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Config file

1. Create a config file where you specify the authentication and configuration details. For example:
   config.txt

   Copy

   Ask AI

   token API_TOKEN
   url https://AXIOM_DOMAIN
   query-rate 1
   query-burst 1
   datasets-rate 1
   datasets-burst 1
   monitors-rate 1
   monitors-burst 1
   

   Replace API_TOKEN with the Axiom API token you have generated. For added security, store the API token in an environment variable.Replace AXIOM_DOMAIN with api.axiom.co if your organization uses the US region, and with api.eu.axiom.co if your organization uses the EU region. For more information, see Regions.
   Optionally, configure the rate and the burst limits at the query, dataset, and monitor levels. The rate limit is the maximum number of requests that your AI agent can make per second. The burst limit is the maximum number of requests that your AI agent can make in a short period (burst) before the rate limit applies to further requests.
2. In the settings of your AI agent, reference the binary file of Axiom MCP Server and the config file you have previously created. For example, if you use the Claude desktop app, add axiom to the mcpServers section of the Claude configuration file. If you use a Mac, the default path is ~/Library/Application Support/Claude/claude_desktop_config.json.
   claude_desktop_config.json

   Copy

   Ask AI

   {
     "mcpServers": {
       "axiom": {
         "command": "PATH_AXIOM_MCP_BINARY",
         "args" : ["--config", "PATH_AXIOM_MCP_CONFIG"]
       }
     }
   }
   

   Replace PATH_AXIOM_MCP_BINARY with the path the binary file of Axiom MCP Server. By default, it’s ~/go/bin/axiom-mcp.Replace PATH_AXIOM_MCP_CONFIG with the path the config file you have previously created.

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Environment variables

{
  "mcpServers": {
    "axiom": {
      "command": "PATH_AXIOM_MCP_BINARY",
      "env": {
        "AXIOM_TOKEN": "API_TOKEN",
        "AXIOM_URL": "https://AXIOM_DOMAIN",
        "AXIOM_QUERY_RATE": "1",
        "AXIOM_QUERY_BURST": "1",
        "AXIOM_DATASETS_RATE": "1",
        "AXIOM_DATASETS_BURST": "1",
        "AXIOM_MONITORS_RATE": "1",
        "AXIOM_MONITORS_BURST": "1"
      }
    }
  }
}

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Ask your AI agent about your data

• “List datasets.”
• “Get the data schema for the dataset logs.”
• “Get the most common status codes in the last 30 minutes in the dataset logs.”