"Datadog - A monitoring and analytics platform for developers and IT operations" matching MCP servers:

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.

Enables agents to discover Mastercard Developers services and access integration guides and API documentation through the Model Context Protocol.

A deployable MCP server template for Cloudflare Workers that provides Google OAuth authentication and comprehensive analytics tracking of tool usage, performance metrics, and user behavior.

Gaudio Lab Audio AI — Stem Separation, DME Separation, AI Text Sync

Turn markdown into designed PDFs with cover page, table of contents, and code blocks that hold across pages. One command from Claude Desktop, Claude Code, Cursor, Cline, Zed, or any MCP-capable client.

Enables AI assistants to access full Datadog observability, including log search, APM trace filtering, smart sampling, and cross-correlation between logs, traces, and metrics.

for tracing and monitoring

Connects AI agents to live observability stacks including Sentry, GitHub, Vercel, Better Stack, and Cloudflare, enabling end-to-end incident investigation, deployment correlation, root cause analysis, and regression triage.

Datadog MCP — 165 tools for metrics, monitors, logs, APM, RUM, incidents, CI/CD, fleet automation. Includes incident-triage-snapshot aggregation tool and 4 workflow Prompts.

Enables natural-language investigation of Datadog data including logs, metrics, monitors, traces, hosts, dashboards, events, and incidents, all through read-only API access.

Enables interaction with Datadog's monitoring and observability platform through the MCP protocol. Supports incident management, monitor status checks, log searches, metrics queries, APM traces, dashboard access, RUM analytics, host management, and downtime scheduling.

Enables interaction with Datadog's monitoring platform to search logs, search trace spans, and perform trace span aggregation for analysis.

A comprehensive read-only MCP server for Datadog, providing 117 tools to query logs, APM, metrics, monitors, dashboards, SLOs, and more, with zero write capabilities for safe AI integration.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.