π₯ Trending Repository: mcp-context-forge
π 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).
π Repository URL: https://github.com/IBM/mcp-context-forge
π Website: https://ibm.github.io/mcp-context-forge/
π Readme: https://github.com/IBM/mcp-context-forge#readme
π Statistics:
π Stars: 1.1K stars
π Watchers: 22
π΄ Forks: 184 forks
π» Programming Languages: Python - JavaScript - Makefile - HTML - Go - Shell
π·οΈ Related Topics:
==================================
π§ By: https://xn--r1a.website/DataScienceM
π 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).
π Repository URL: https://github.com/IBM/mcp-context-forge
π Website: https://ibm.github.io/mcp-context-forge/
π Readme: https://github.com/IBM/mcp-context-forge#readme
π Statistics:
π Stars: 1.1K stars
π Watchers: 22
π΄ Forks: 184 forks
π» Programming Languages: Python - JavaScript - Makefile - HTML - Go - Shell
π·οΈ 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
==================================
π§ By: https://xn--r1a.website/DataScienceM
β€2
π₯ Trending Repository: mcp-context-forge
π 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).
π Repository URL: https://github.com/IBM/mcp-context-forge
π Website: https://ibm.github.io/mcp-context-forge/
π Readme: https://github.com/IBM/mcp-context-forge#readme
π Statistics:
π Stars: 1.7K stars
π Watchers: 21
π΄ Forks: 215 forks
π» Programming Languages: Python - HTML - JavaScript - Makefile - Go - Shell
π·οΈ Related Topics:
==================================
π§ By: https://xn--r1a.website/DataScienceM
π 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).
π Repository URL: https://github.com/IBM/mcp-context-forge
π Website: https://ibm.github.io/mcp-context-forge/
π Readme: https://github.com/IBM/mcp-context-forge#readme
π Statistics:
π Stars: 1.7K stars
π Watchers: 21
π΄ Forks: 215 forks
π» Programming Languages: Python - HTML - JavaScript - Makefile - Go - Shell
π·οΈ 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
==================================
π§ By: https://xn--r1a.website/DataScienceM
π€π§ MLOps Basics: A Complete Guide to Building, Deploying and Monitoring Machine Learning Models
ποΈ 30 Oct 2025
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ποΈ 30 Oct 2025
π 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 β 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 ...
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π Category: PRODUCT MANAGEMENT
π Date: 2025-11-28 | β±οΈ Read time: 10 min read
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π Category: PRODUCT MANAGEMENT
π Date: 2025-11-28 | β±οΈ 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.
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Forwarded from Machine Learning with Python
A guide to Loop Engineering has been released β 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. ππ€
The author notes that most people still use Claude Code, Codex, Cursor, and Grok as a regular chat: prompt β wait β copy β correct β 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. π οΈβοΈ
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. πβ
"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. ππ§
The repository is available on GitHub.
Repository: https://github.com/cobusgreyling/loop-engineering
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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. ππ€
The author notes that most people still use Claude Code, Codex, Cursor, and Grok as a regular chat: prompt β wait β copy β correct β 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. π οΈβοΈ
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. πβ
"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. ππ§
The repository is available on GitHub.
Repository: https://github.com/cobusgreyling/loop-engineering
#LoopEngineering #AI #Agents #GitHub #DevOps #Automation
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
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If youβre prepping for cloud, dev, or AI roles this year, these free kits cover the gaps most people skip β cert basics, hands-on labs, and mock exams. No signup traps, no hidden fees.
π Cert E-Book β covers Cisco & AWS fundamentals, good for first-time cert takers
β https://bit.ly/4yrk1Ti
πͺ Online Free Course β structured path, works as a refresher before exams
β https://bit.ly/4hUprRP
βοΈ Free AI Materials β LLM basics to fine-tuning practice notebooks
β https://bit.ly/4yt1iXy
π Cloud Study Guide β cheat-sheet style, handy for interview prep
β https://bit.ly/4el4Eod
π§ Free Mock Exam β test yourself before booking the real thing
β https://bit.ly/4sbWlkl
π Save this or forward it to your dev/study group β good resources are worth sharing. πͺ
π Community: https://chat.whatsapp.com/CS7VOvQCLZG5BJPazBGm1v
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