mcp-server-logs-sieve
Provides tools for querying, summarizing, and tracing logs stored in Elasticsearch, enabling AI assistants to analyze observability data directly.
Provides tools for querying, summarizing, and tracing logs stored in Elasticsearch, enabling AI assistants to analyze observability data directly.
Enables AI assistants to query, summarize, and trace logs from Google Cloud Logging to accelerate incident response and debugging.
Allows AI assistants to interact with Grafana Loki to query, summarize, and trace logs, helping to identify failure patterns and follow traces across services.
mcp-server-logs-sieve
mcp-server-logs-sieve is an MCP server that lets AI assistants query logs directly from your observability backend.
Ask debugging questions in plain language, and let Logs Sieve pull the exact logs and context for you.
Why this exists
During incidents, a lot of time goes into repetitive steps:
finding the right log source
narrowing the time window
spotting recurring failure patterns
following one trace across services
Logs Sieve packages those workflows into four tools: query_logs, summarize_logs, trace_request, and list_log_sources.
Related MCP server: Azure Logs MCP
Supported providers
Google Cloud Logging (
gcp)AWS CloudWatch Logs (
aws)Azure Monitor Logs (
azure)Grafana Loki (
loki)Elasticsearch (
elasticsearch)
Prerequisites
⚠️ Node.js 20 or above is required.
This package uses ES modules and dependencies that need Node.js 20+. If you see
ERR_MODULE_NOT_FOUNDerrors, check your Node version withnode -vand upgrade if needed.This applies whether you run via
npx, install globally, or use from source.
Quick MCP config
Example .mcp.json:
{
"mcpServers": {
"logs-sieve": {
"command": "npx",
"args": ["-y", "mcp-server-logs-sieve@latest", "--provider", "gcp"]
}
}
}If you are running from this repo source directly, you can still use node ./bin/mcp-server-logs-sieve.js --provider gcp.
First-time setup: On first use, npx needs to download and install the package (~40s). Claude Code may time out waiting for this. Run the following once in your terminal to prime the cache before adding it to your MCP config:
npx mcp-server-logs-sieve@latest --provider gcp
# (Ctrl+C once it starts — you just need the install to complete)After that, Claude Code will start the server instantly from the npx cache.
After updating config, restart your MCP client and confirm with /mcp.
Provider auth and env vars
See provider-specific setup and auth docs:
For Elasticsearch API compatibility headers:
export ELASTICSEARCH_COMPAT_VERSION=8CLI usage
The package also includes a CLI for direct terminal usage:
mcp-server-logs-sieve query --provider gcp --scope my-project --last 1h --filter "payment failed"
mcp-server-logs-sieve summarize --provider gcp --scope my-project --last 24h
mcp-server-logs-sieve trace --provider gcp --scope my-project --trace <trace-id>
mcp-server-logs-sieve sources --provider gcp --scope my-projectDocumentation
Contributing
Contributions are welcome.
Maintenance
Related MCP Connectors
Query application logs, traces, and metrics from your AI coding assistant via Foam's MCP server.
Hosted MCP server connecting claude.ai, ChatGPT and other AI apps to your own computer
- QuallaaOAuthcom.quallaa
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
Real-time chat for AI agents. Claude Code, Cursor, Cline and Codex join channels over MCP.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceAn MCP server that allows AI assistants to access AWS CloudWatch logs by listing log groups and reading log entries.27-
- AlicenseBqualityDmaintenanceEnables querying Azure Application Insights logs by order number through natural language. Provides secure access to Azure Monitor logs with comprehensive error handling and rate limiting.11MIT
- FlicenseAqualityDmaintenanceEnables text-to-image generation, image editing, and multi-image composition using Google's Gemini 2.5 Flash Image API. Supports flexible aspect ratios and character consistency across generations.1-
- AlicenseAqualityDmaintenanceMCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context.7100MIT