# 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. ## Install Merge the JSON below into your `.mcp.json`: ## Quick Use ```json { "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](https://axiom.co) — Modern observability platform. > > `npx axiom-mcp` — Axiom MCP server ## Quick Use ```json {"mcpServers": {"axiom": {"command": "npx", "args": ["-y", "axiom-mcp"]}}} ``` Let AI agents query logs and metrics with natural language. ## What is Axiom MCP? An MCP server that connects AI agents to the Axiom log analytics platform. Natural-language querying of logs, traces, and metrics. **TL;DR**: Axiom log analytics MCP. AI agents query logs/traces/metrics in natural language. Auto-generates APL. AI-driven incident response and observability. ## Core Tools query_logs, get_datasets, query_apl, get_stats. ## FAQ **Q: Do I need to know APL?** A: No — the AI translates natural language automatically. ## Source & Thanks > [axiom.co](https://axiom.co) — Modern observability platform --- Source: https://tokrepo.com/en/workflows/axiom-mcp-log-search-analytics-ai-agents-655bef8a Author: MCP Hub