"How to fully utilize Docket application or platform" matching MCP servers:

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

Demonstrates agent-native platform onboarding with human-in-the-loop API key provisioning, plus live usage and rate-limit queries via Anthropic Admin APIs.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables DevOps operators to query and operate the Sigma Streaming Platform from any AI client such as Claude Desktop, Cursor, or Kiro.

Enables approval-gated incident response workflows that gather evidence through read-only MCP tools, perform idempotent writes, and preserve a durable audit trail.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

Provides AI agents with real-time access to live Azure infrastructure, including AKS cluster health, resource management, policy validation, and Terraform analysis through a Model Context Protocol interface.

Enables AI assistants to interact with SMB platform APIs for querying business data, managing tasks, accessing connectors, dashboards, and monitoring security.

A FastAPI-based server that enables executing SQL queries, managing database connections, and retrieving analytics reports through MCP-integrated endpoints. It allows users to interact with database schemas, performance metrics, and access logs using structured queries.

Enables reading and building Splunk dashboards via the management REST API, using SSO for permissions and supporting both Studio and Classic formats.

Enables users to inspect ephemeral GitHub Actions runner fleet status, SLOs, incidents, capacity recommendations, and cost evidence through read-only MCP tools, without allowing infrastructure or cluster mutations.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

A high-performance MCP server integrated with a Django analytics dashboard, featuring 19 tools for AI interaction tracking, AST code analysis, and real-time token efficiency metrics.

Enables comprehensive NIST Cybersecurity Framework 2.0 assessments with 40+ MCP tools for maturity scoring, gap analysis, implementation planning, risk assessment, and executive reporting across 740 security questions.

Competitive intelligence platform with 24 tools. Monitor competitor pricing, content, positioning, tech stacks, and AI visibility — track how ChatGPT, Claude, and Gemini rank your brand.

Provides read-only observability and operational insight into a MuleSoft Anypoint Platform estate, enabling natural-language queries for application logs, archived log search, Runtime Manager inventory, API Manager instances, and Exchange assets using your own credentials.

Enables monitoring and analysis of local application log files with real-time tailing, error tracking, and search capabilities. Perfect for debugging Node.js applications, web servers, or any application that writes to log files through natural language commands.