openobserve-mcp
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Alternatives to openobserve-mcp
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Related Servers
- AlicenseNot gradedqualityBmaintenanceAn MCP server that enables AI assistants to query and explore your OpenObserve observability data. Provides read-only access to logs, metrics, and traces for analysis and troubleshooting.5MIT
- AlicenseNot gradedqualityDmaintenanceMCP server for querying observability data from Elasticsearch, SkyWalking, and Prometheus/VictoriaMetrics, enabling AI models to search logs, traces, and metrics across environments.9MIT
- FlicenseNot gradedqualityCmaintenanceMCP server for observability that provides tools for log search, metrics inspection, SQL querying, incident summaries, and service discovery.-
- AlicenseAqualityDmaintenanceMCP server that gives AI agents access to your application's OpenTelemetry traces for querying, analysis, and debugging.57 npm2MIT
- AlicenseBqualityCmaintenanceA read-only MCP server for OpenObserve Community Edition that works over the REST API. Provides tools for searching logs, traces, stream schemas, and dashboards - no Enterprise license required.8196 PyPI17GPL 3.0
- AlicenseAqualityBmaintenanceMCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.613 npmMIT
TDQS
Scored across 8 tools
Each tool targets a distinct aspect of OpenObserve: streams, schema, org summary, logs, traces, metrics. Search vs. aggregate vs. query are clearly differentiated by descriptions, and search_traces vs. get_trace are separate listing vs. detail operations.
All tool names use snake_case with a verb_noun structure (list_, get_, search_, aggregate_, query_). The verbs accurately reflect the operation, and the nouns denote the target resource. This is highly predictable.
With 8 tools covering streams, schema, logs, traces, and metrics, the surface is well-scoped without being bloated. Each tool fills a necessary role for an observability MCP server.
The set provides a comprehensive read-only query surface: listing streams, inspecting schemas, searching and aggregating logs, listing traces with details, and querying metrics. No obvious dead ends or missing critical operations for the core domain.