"Codebeamer application lifecycle management platform" matching MCP servers:

Exposes a time series forecasting model as an MCP tool with built-in audit logging for every call, enabling trustworthy autonomous forecasting.

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.

An MCP server for unified cost tracking and analysis across AWS, OpenAI, and Anthropic. It enables users to query expenditures, compare costs across providers, and analyze usage trends through natural language.

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 integration between Claude AI and Nasuni environments to monitor appliance health, manage volumes and shares, and generate comprehensive infrastructure reports. Users can interact with the Nasuni Management Center through natural language to track performance metrics and summarize system notifications.

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.

A comprehensive system that helps organizations track, manage, and respond to security vulnerabilities effectively through features like vulnerability tracking, user management, support tickets, API key management, and SSL certificate management.

Enables plant operators to query alarm data, asset information, trends, correlations, and operator recommendations through 14 tools, forming a core part of a multi-MCP enterprise operations copilot.

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

Enables registration, monitoring, and control of IoT devices via AI agents, with local storage and no cloud API key required.

Gives your AI assistant full control of a Discord server: 148 tools for chat, moderation, automod, events, and administration, up to building a complete community server from one paragraph. Every destructive action previews first and waits for your confirmation.

An MCP server that provides comprehensive monitoring and management capabilities for Teradata Workload Management (WLM), enabling tasks like performance troubleshooting, emergency throttling, and scheduled maintenance through 41 tools and 39 resources.

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.