MCP Servers
Agentic Radar
A security scanner for your LLM agentic workflows
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"Automated summary for AI agents and search engines."
Agentic Radar
A security scanner for your LLM agentic workflows
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CodeRabbitA security scanner for your LLM agentic workflows
"Automated summary for AI agents and search engines."
A security scanner for your LLM agentic workflows
{"id":"1568109f-9772-4998-b681-840cbbc7e7d6","title":"Agentic Radar","description":"Agentic Radar provides a Model Context Protocol server that monitors and analyzes agent activities and interactions within development environments, offering real-time insights into agent performance, token usage, and operational efficiency. It helps developers debug, optimize, and understand the complex behaviors of AI coding assistants by capturing detailed logs and telemetry.","schemaDescription":"A Model Context Protocol server for collecting and visualizing telemetry data from AI coding agents, providing developers with actionable insights into agent execution, resource consumption, and decision-making processes.","dateModified":"2026-04-03","author":"splx-ai","authorGithub":"https://github.com/splx-ai","license":"Unknown","transport":"Unknown","language":"Python","difficulty":"intermediate","tags":["mcp-server","agent-monitoring","telemetry","observability","ai-debugging"],"tokenImpact":"Moderate — 1,000–3,000 tokens per call, monitor quota during lockouts.","useCases":["Monitor real-time token usage and API calls made by AI agents.","Visualize agent decision paths and tool invocations for debugging.","Track agent performance metrics across different projects and tasks.","Identify bottlenecks or inefficient agent behaviors in complex workflows.","Generate reports on agent activity and resource consumption."],"exampleCommand":"pip install agentic-radar && python -m agentic_radar.server","mcpConfig":{"mcpServers":{"agentic-radar":{"command":"python","args":["-m","agentic_radar.server"],"env":{}}}},"compatibility":["Google Antigravity IDE"],"copyButtonText":"Copy mcp_config.json","artifactsProduced":["Agent activity logs","Telemetry data","Performance reports","Token usage graphs"],"faq":[{"question":"What can you do with Agentic Radar?","answer":"Agentic Radar allows you to gain deep insights into your AI agents' operations, providing detailed logging, performance metrics, and visualization tools to understand how agents make decisions, consume resources, and interact with the environment. It helps optimize agentic workflows."},{"question":"Which AI assistants and IDEs are compatible with Agentic Radar?","answer":"Agentic Radar is designed to integrate with AI assistants and IDEs that support the Model Context Protocol, allowing it to collect telemetry data from agent interactions. It is compatible with Google Antigravity IDE and other MCP-compliant environments."},{"question":"How do I install and configure Agentic Radar?","answer":"To install, run `pip install agentic-radar`. Configuration typically involves integrating its monitoring capabilities into your agent's execution environment. For server mode, you would run `python -m agentic_radar.server` and configure your IDE to connect to this server via MCP settings, specifying the server address if remote."}]}🚀 The fast, Pythonic way to build MCP servers and clients.
MCP web search using perplexity without any API KEYS
一个基于 MCP (Model Context Protocol) 的邮件服务，支持 LLM 发送带附件的电子邮件及在指定目录中搜索文件。提供安全的 SMTP 传输、多收件人支持和附件模式匹配搜索功能，适用于 Gmail、Outlook、Yahoo、QQ 邮箱和网易 126 邮箱等主流邮箱服务。
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