MCP ConfigsApr 8, 2026·2 min read

Axiom MCP — Log Search and Analytics for AI Agents

MCP server that gives AI agents access to Axiom log analytics. Query logs, traces, and metrics through natural language for AI-powered observability and incident response.

MC
MCP Hub · Community
Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

{
  "mcpServers": {
    "axiom": {
      "command": "npx",
      "args": ["-y", "axiom-mcp"],
      "env": {
        "AXIOM_TOKEN": "xaat-...",
        "AXIOM_ORG_ID": "your-org"
      }
    }
  }
}

Now ask your AI agent:

"Show me error logs from the last hour"
"What caused the spike in 500 errors at 3pm?"
"Find all requests with latency > 2 seconds"
"Compare today's error rate with yesterday"

What is Axiom MCP?

Axiom MCP is a Model Context Protocol server that connects AI agents to Axiom's log analytics platform. Agents can query logs, traces, and metrics using natural language — no APL (Axiom Processing Language) knowledge needed. The agent translates questions into APL queries, executes them, and interprets results. Ideal for AI-powered incident response and observability.

Answer-Ready: Axiom MCP gives AI agents log search and analytics access. Query logs, traces, and metrics via natural language. Agent auto-generates APL queries. AI-powered incident response and observability. Works with Claude Code and Cursor.

Best for: DevOps teams wanting AI-assisted log analysis and incident response. Works with: Claude Code, Cursor, Claude Desktop. Setup time: Under 3 minutes.

Core Tools

Tool What It Does
query_logs Search logs with APL or natural language
get_datasets List available log datasets
query_apl Execute raw APL queries
get_stats Summary statistics for a dataset

Use Cases

Use Case Example Query
Incident Response "What errors appeared in the last 30 minutes?"
Performance "Average response time for /api/users endpoint today"
Debugging "Show me all requests from user_id 12345"
Trending "Compare error rates: this week vs last week"
Anomaly Detection "Any unusual spikes in 4xx errors?"

Example Interactions

Error Investigation

User: "Why are users getting 500 errors?"
Agent: [calls query_logs with APL filter for status=500]
Agent: "I found 47 500 errors in the last hour.
        90% are from the /api/payments endpoint.
        Root cause: ConnectionRefusedError to payment-service:8080.
        The payment service appears to be down."

Performance Analysis

User: "Is the API getting slower?"
Agent: [calls query_apl with percentile analysis]
Agent: "P95 latency increased from 180ms to 450ms
        starting at 2:30 PM. The slowdown correlates
        with a deployment at 2:28 PM (commit abc123)."

FAQ

Q: Do I need to know APL? A: No, the AI agent translates natural language to APL. But APL knowledge helps for complex queries.

Q: What log platforms does it support? A: This MCP is specifically for Axiom. For other platforms, look for Datadog MCP or Sentry MCP.

Q: Can it create alerts? A: Currently read-only — query and analyze. Alert creation would need the Axiom API directly.

🙏

Source & Thanks

Built for Axiom — Modern observability platform.

npx axiom-mcp — Axiom MCP server

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