MCP gateway with authorization, credential injection, audit logging, and output policies.
Local MCP server providing AI-driven access to Dynatrace observability data via natural language queries.
Key Features: AI-powered DQL generation and explanation Browser-based OAuth Authorization Code Flow authentication Token storage in OS keychain or file system MCP server providing live status and incident details for 3355 software services from official status pages.
Key Features: Access normalized live status for 3355 major software services Fetch structured incident details automatically for non-operational services Cache status data with 60-second expiry and option to bypass cache Java MCP server providing full observability and management of Langfuse traces, sessions, prompts, datasets, and evaluations.
Key Features: Paginated trace and session querying with filtering Error-level exception tracking and detailed retrieval Full prompt lifecycle management with versioning and labels MCP server proxying Sentry API for developer workflows, enabling AI agents to query errors, issues, and performance data.
Key Features: Middleware MCP server for Sentry API Supports AI-powered natural language search with LLM providers Compatible with remote and stdio transports Multi-tenant MCP platform with OAuth 2.1, Entra SSO, RBAC and audit logging.
Tamper-evident audit log and observability server for AI agents with SHA-256 hash chaining and real-time dashboard.
Key Features: SHA-256 hash-chained, append-only audit log Cryptographically verifiable event chain to detect tampering Multiple integration options: OpenTelemetry, OpenClaw, MCP, SDKs Access and manage Grafana dashboards, datasources, queries, incidents, and permissions via MCP.
Key Features: Dashboard search, summary, property extraction, and updates Prometheus and Loki querying with metadata access Incident creation, listing, and activity management Voris privacy-native web analytics for AI agents: query metrics & citations, scaffold tracking.
MCP server for Altmetric APIs - track research attention across news, policy, social media, and more
MCP server for AI agent evaluation with trace logging, output quality checks, cost tracking, and a real-time dashboard.
Key Features: Hierarchical span trace logging with latency, token usage, and cost 13 built-in evaluation rules including PII and prompt injection detection Cost aggregation and budget threshold alerts Independent monitoring: status, monitors, and incidents from your StackWitness workspace.