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    A template for deploying MCP servers as Cloudflare Workers with integrated LogPush and R2 storage for detailed execution logging. It enables remote tool execution and provides utilities for retrieving logs directly from Cloudflare R2 buckets.
    ISC
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    Enables centralized management and monitoring of multiple distributed worker MCP servers. Provides tools to list workers, get status of all workers, and query specific worker status.
    5
    -
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    A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
    100
    3
    MIT
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    A monorepo of MCP toolkits for Cloudflare Workers, providing over 630 tools across SaaS providers and AWS, with composite tools for security, incident response, billing, and cloud cost optimization.
    MIT
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    Provides a deployable template that turns a Cloudflare Workers account into a hosted MCP endpoint with OAuth-gated private tools, auto-generated docs, health checks, rate limiting, and a server-rendered monitoring dashboard.
    -
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    Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.
    1
    MIT
  • F
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    maintenance
    Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.
    -
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    Remote MCP deployment scaffold for Skylight's MCP server, hosted on Cloudflare Workers and Containers, enabling HTTP access to the stdio-based Ruby MCP server.
    MIT
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    Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.
    1,312 npm
    MIT
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    maintenance
    Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.
    5
    MIT