observe-mcp
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- FlicenseNot gradedqualityCmaintenanceMCP server for observability that provides tools for log search, metrics inspection, SQL querying, incident summaries, and service discovery.-
- AlicenseAqualityCmaintenanceMCP server that enables querying an OpenObserve instance for logs, traces, and metrics via tools like search_logs, search_traces, get_trace, and query_metrics, supporting natural-language-driven observability workflows.833 npmMIT
- AlicenseNot gradedqualityNot gradedmaintenanceA Model Context Protocol server that provides access to Observe API functionality, enabling LLMs to execute OPAL queries, manage datasets/monitors, and leverage vector search for documentation and troubleshooting runbooks.1-

opal-mcpofficial
AlicenseNot gradedqualityDmaintenanceMCP server for interacting with the Opal Security platform, enabling operations like managing access rules, apps, and bundles via natural language.30 npm4Apache 2.0- 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
- 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.816GPL 3.0
TDQS
Scored across 7 tools
Tools have distinct purposes overall, but get_dataset_schema and inspect_dataset both deal with field discovery, potentially causing confusion. search_entity_logs and search_service_logs are similarly structured but target different scopes.
Most tools use snake_case with verb-first naming, but observe_docs and observe_query break the pattern by using the server name prefix instead of a verb. get_dataset_schema and inspect_dataset share 'dataset' but use different verbs, causing slight inconsistency.
Seven tools is well-scoped for a query-focused Observe MCP server, covering dataset discovery, schema inspection, query execution, and log searching without being overwhelming.
The tool surface covers core querying tasks: listing datasets, inspecting schemas, running queries, and searching logs. Missing might be dataset creation or alert management, but these are outside the apparent query-focused scope.