"facebook ads" matching MCP servers:

Enables autonomous AI agents to safely inspect, optimize, and manage live search campaigns through 38 purpose-built tools covering bids, budgets, keywords, RSAs, assets, and negative keyword harvesting. Bundles two-layer Pydantic execution shields with bounded bid ceilings and fixed stepping, a preflight gatekeeper, and W3C distributed tracing that separates upstream Google Ads API latency from local execution overhead.

Enables LLM clients to query AWS CloudWatch Logs and Alarms through MCP tools.

Provides read-only monitoring, inspection, and root-cause analysis of Azure Data Factory resources, including factories, pipelines, and pipeline runs, through MCP tools.

A read-only MCP server that lets an AI assistant inspect a single AWS lab instance's EC2 health, recent system/nginx errors from CloudWatch, and nginx service status via SSM, with strict allowlisting and no generic shell access.

A comprehensive Model Context Protocol (MCP) server for New Relic monitoring, observability, and management operations.

Enables Claude Desktop to interact with 57 AWS services using over 200 tools and local machine profiles. It supports multi-profile configurations and features a read-only safe mode by default to manage infrastructure like EC2, S3, and Lambda securely.

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

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.

Acts as an MCP gateway between AI agents and upstream tool servers, evaluating YAML policies on every tool call, injecting real credentials at the last mile, scanning requests and responses for secrets, PII, and prompt injection, and recording each action in a tamper-evident audit log. Also supports HTTP forward-proxy governance with rate limiting, cost tracking, and policy replay against historical audit data.

A read-only Model Context Protocol server that exposes over 60 AWS tools across services like EC2, S3, and IAM for AI agent interaction. It features multi-region support, resource caching, and audit logging to provide secure, AI-ready access to AWS infrastructure data.

A read-only MCP server that exposes tools to query Datadog monitors and logs, and AWS CloudWatch Logs, and to group recurring errors by fingerprint. Designed for use with Claude Code to diagnose issues and propose fixes.

MCP servers for real-time development monitoring and interactive pair programming.

Enables any MCP client to watch a running DSH agent and steer it mid-flight, streaming thinking, tool and file notifications while sharing intent and exposing a floor lock that denies the agent's writes while held. It also lets clients interrupt the current turn with an injected alert and delegate reviews through an on-disk inbox.

MCP server that reports AI agent costs (tokens, latency, dollars) with per-tenant isolation via OAuth, and includes an ADK agent for natural-language queries.

A read-only MCP server for safe, structured investigation of AWS serverless resources, providing curated tools for tracing dependencies, permissions, and failures without exposing raw SDK access.

Enables AI clients to read live drone status, telemetry, and parameters, and to control drone operations with scoped permissions, confirmation steps, and audit trails.

Enables AI agents to diagnose and analyze AWS serverless infrastructure through Model Context Protocol, providing access to CloudWatch logs, Lambda functions, DynamoDB tables, IAM policies, and Bedrock-powered incident root-cause analysis.

Enables secure tool discovery and execution on AWS Lambda with role-based access control, command injection defense, and sensitive data redaction, allowing managed CloudWatch log queries and Terraform operations through a standard MCP interface.

Enables AI agents to perform root cause analysis on SAP systems by querying Azure Log Analytics data, offering schema discovery, validated KQL execution, result analysis, and automated 8-step RCA workflows.

Enables read-only monitoring and root-cause analysis of Azure Data Factory resources through MCP, allowing users to inspect factories, pipelines, and pipeline runs and diagnose failures via natural language.