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"How to work with Cocos .csd files" matching MCP servers:

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    A Model Context Protocol server that enables AI tools to automatically log their activities with detailed metrics like timestamps, token usage, and costs into daily markdown worklog files.
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    MIT
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    A powerful log bridging tool that synchronizes log information between Cocos Creator editor and Cursor AI, helping developers analyze and solve problems more effectively.
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    MIT
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    Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.
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    Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.
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    MIT
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    MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.
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    Apache 2.0
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    An MCP server for AI-powered log analysis that enables parsing, searching, and debugging across nine log formats directly within Claude. It features automated error extraction, sensitive data scanning, and streaming support for large log files.
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    MIT
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    Enables LLMs to analyze network packet captures (PCAP files) from local or remote sources through a modular architecture. Supports DNS traffic analysis with structured JSON responses for network security and troubleshooting tasks.
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    iOS leak hunting and performance investigation. Reads .memgraph and .trace files, classifies retain cycles against a 34-pattern catalog with Swift fix templates, bridges to source via SourceKit-LSP. 28 MCP tools, 34 catalog resources, 5 investigation prompts.
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    Apache 2.0
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    Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.
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    MIT
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    Enables AI assistants to automatically inspect and analyze application runtime log files for debugging and troubleshooting. Supports monitoring multiple log directories simultaneously with tools for listing, reading, searching, and paginating through log files.
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    MIT
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    MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.
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    GPL 3.0
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    Enables LLMs to analyze network packet captures (PCAP files) from local or remote sources. Provides structured analysis of network protocols like DNS traffic through a modular architecture using scapy.
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    MIT