🔥 Trending Repository: mcp-context-forge
📝 Description: A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
🔗 Repository URL: https://github.com/IBM/mcp-context-forge
🌐 Website: https://ibm.github.io/mcp-context-forge/
📖 Readme: https://github.com/IBM/mcp-context-forge#readme
📊 Statistics:
🌟 Stars: 1.1K stars
👀 Watchers: 22
🍴 Forks: 184 forks
💻 Programming Languages: Python - JavaScript - Makefile - HTML - Go - Shell
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
🔗 Repository URL: https://github.com/IBM/mcp-context-forge
🌐 Website: https://ibm.github.io/mcp-context-forge/
📖 Readme: https://github.com/IBM/mcp-context-forge#readme
📊 Statistics:
🌟 Stars: 1.1K stars
👀 Watchers: 22
🍴 Forks: 184 forks
💻 Programming Languages: Python - JavaScript - Makefile - HTML - Go - Shell
🏷️ Related Topics:
#python #docker #kubernetes #devops #jwt #tools #ai #api_gateway #mcp #gateway #asyncio #federation #agents #observability #authentication_middleware #fastapi #prompt_engineering #generative_ai #llm_agents #model_context_protocol
==================================
🧠 By: https://t.iss.one/DataScienceM
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🔥 Trending Repository: mcp-context-forge
📝 Description: A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
🔗 Repository URL: https://github.com/IBM/mcp-context-forge
🌐 Website: https://ibm.github.io/mcp-context-forge/
📖 Readme: https://github.com/IBM/mcp-context-forge#readme
📊 Statistics:
🌟 Stars: 1.7K stars
👀 Watchers: 21
🍴 Forks: 215 forks
💻 Programming Languages: Python - HTML - JavaScript - Makefile - Go - Shell
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
🔗 Repository URL: https://github.com/IBM/mcp-context-forge
🌐 Website: https://ibm.github.io/mcp-context-forge/
📖 Readme: https://github.com/IBM/mcp-context-forge#readme
📊 Statistics:
🌟 Stars: 1.7K stars
👀 Watchers: 21
🍴 Forks: 215 forks
💻 Programming Languages: Python - HTML - JavaScript - Makefile - Go - Shell
🏷️ Related Topics:
#python #docker #kubernetes #devops #jwt #tools #ai #api_gateway #mcp #gateway #asyncio #federation #agents #observability #authentication_middleware #fastapi #prompt_engineering #generative_ai #llm_agents #model_context_protocol
==================================
🧠 By: https://t.iss.one/DataScienceM
🤖🧠 MLOps Basics: A Complete Guide to Building, Deploying and Monitoring Machine Learning Models
🗓️ 30 Oct 2025
📚 AI News & Trends
Machine Learning models are powerful but building them is only half the story. The true challenge lies in deploying, scaling and maintaining these models in production environments – a process that requires collaboration between data scientists, developers and operations teams. This is where MLOps (Machine Learning Operations) comes in. MLOps combines the principles of DevOps ...
#MLOps #MachineLearning #DevOps #ModelDeployment #DataScience #ProductionAI
🗓️ 30 Oct 2025
📚 AI News & Trends
Machine Learning models are powerful but building them is only half the story. The true challenge lies in deploying, scaling and maintaining these models in production environments – a process that requires collaboration between data scientists, developers and operations teams. This is where MLOps (Machine Learning Operations) comes in. MLOps combines the principles of DevOps ...
#MLOps #MachineLearning #DevOps #ModelDeployment #DataScience #ProductionAI
🏆 Ultimate DevOps: 150 Commands & Code
📢 Master DevOps with 150 essential commands! This guide simplifies complex tools and concepts, offering practical examples for your journey into efficient software delivery.
⚡ Tap to unlock the complete answer and gain instant insight.
━━━━━━━━━━━━━━━
By: @DataScienceM ✨
📢 Master DevOps with 150 essential commands! This guide simplifies complex tools and concepts, offering practical examples for your journey into efficient software delivery.
⚡ Tap to unlock the complete answer and gain instant insight.
━━━━━━━━━━━━━━━
By: @DataScienceM ✨
Telegraph
Ultimate DevOps: 150 Commands & Code
Lesson: The Ultimate DevOps Command Reference (150 Examples) #DevOps #Linux #Git #Docker #Kubernetes #Ansible #Terraform #CICD #AWS #Cloud --- What is DevOps?
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📌 The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation
🗂 Category: PRODUCT MANAGEMENT
🕒 Date: 2025-11-28 | ⏱️ Read time: 10 min read
Discover how a unified Product Health Score, powered by integrated monitoring and n8n automation, can align product, growth, and engineering teams. This single-signal approach streamlines incident management and successfully reduced critical incidents by an impressive 35%, creating a more stable and reliable product.
#ProductHealth #Automation #n8n #IncidentManagement #DevOps
🗂 Category: PRODUCT MANAGEMENT
🕒 Date: 2025-11-28 | ⏱️ Read time: 10 min read
Discover how a unified Product Health Score, powered by integrated monitoring and n8n automation, can align product, growth, and engineering teams. This single-signal approach streamlines incident management and successfully reduced critical incidents by an impressive 35%, creating a more stable and reliable product.
#ProductHealth #Automation #n8n #IncidentManagement #DevOps
❤4
Forwarded from Machine Learning with Python
A guide to Loop Engineering has been released — a new approach to working with AI agents
The repository loop-engineering has been published, offering a paradigm shift: instead of manually prompting AI agents, the developer designs a cycle that does this automatically. 🔄🤖
The author notes that most people still use Claude Code, Codex, Cursor, and Grok as a regular chat: prompt → wait → copy → correct → prompt again. Loop Engineering proposes to stop being a "nanny" for the agent and instead build a system where agents work, check, correct, and escalate on their own. 🛠️⚙️
The repository includes ready-made cycles for daily triage, PR, CI, dependencies, changelog, and issues. It includes CLI for creating cycles, evaluating tokens, auditing the repository, and safely running agents via GitHub Actions. 📋✅
"Prompt engineering was about how to write better prompts. Loop engineering is about creating a system where agents continue to work without your supervision at every step," the description says. 🚀🧠
The repository is available on GitHub.
Repository: https://github.com/cobusgreyling/loop-engineering
#LoopEngineering #AI #Agents #GitHub #DevOps #Automation
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The repository loop-engineering has been published, offering a paradigm shift: instead of manually prompting AI agents, the developer designs a cycle that does this automatically. 🔄🤖
The author notes that most people still use Claude Code, Codex, Cursor, and Grok as a regular chat: prompt → wait → copy → correct → prompt again. Loop Engineering proposes to stop being a "nanny" for the agent and instead build a system where agents work, check, correct, and escalate on their own. 🛠️⚙️
The repository includes ready-made cycles for daily triage, PR, CI, dependencies, changelog, and issues. It includes CLI for creating cycles, evaluating tokens, auditing the repository, and safely running agents via GitHub Actions. 📋✅
"Prompt engineering was about how to write better prompts. Loop engineering is about creating a system where agents continue to work without your supervision at every step," the description says. 🚀🧠
The repository is available on GitHub.
Repository: https://github.com/cobusgreyling/loop-engineering
#LoopEngineering #AI #Agents #GitHub #DevOps #Automation
✨ Join Best TG Channels https://t.iss.one/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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