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infrastructure#agent📝 BlogAnalyzed: Jan 15, 2026 04:30

Building Your Own MCP Server: A Deep Dive into AI Agent Interoperability

Published:Jan 15, 2026 04:24
1 min read
Qiita AI

Analysis

The article's premise of creating an MCP server to understand its mechanics is a practical and valuable learning approach. While the provided text is sparse, the subject matter directly addresses the critical need for interoperability within the rapidly expanding AI agent ecosystem. Further elaboration on implementation details and challenges would significantly increase its educational impact.
Reference

“Claude Desktop and other AI agents use MCP (Model Context Protocol) to connect with external services.”

PermalinkQiita AI
Research#llm📝 BlogAnalyzed: Dec 25, 2025 11:34

What is MCP (Model Context Protocol)?

Published:Dec 25, 2025 11:30
1 min read
Qiita AI

Analysis

This article introduces MCP (Model Context Protocol) and highlights the challenges in current AI utilization. It points out the need for individual implementation for each combination of AI models and external systems, leading to a multiplicative increase in integration complexity as systems and AI models grow. The lack of compatibility due to different connection methods and API specifications for each AI model is also a significant issue. The article suggests that MCP aims to address these problems by providing a standardized protocol for AI model integration, potentially simplifying the development and deployment of AI-powered systems. This standardization could significantly reduce the integration effort and improve the interoperability of different AI models.
Reference

“AI models have different connection methods and API specifications, lacking compatibility.”

PermalinkQiita AI
Research#llm📝 BlogAnalyzed: Dec 25, 2025 17:44

Integrating MCP Tools and RBAC into AI Agents: Implementation with LangChain + PyCasbin

Published:Dec 25, 2025 08:05
1 min read
Zenn LLM

Analysis

This article discusses implementing Role-Based Access Control (RBAC) in LLM-powered AI agents using the Model Context Protocol (MCP). It highlights the security risks associated with autonomous tool usage by LLMs without proper authorization and demonstrates how PyCasbin can be used to restrict LangChain ReAct agents' actions based on roles. The article focuses on practical implementation, covering HTTP + SSE communication using MCP and RBAC management with PyCasbin. It's a valuable resource for developers looking to enhance the security and control of their AI agent applications.
Reference

“本記事では、MCP (Model Context Protocol)を使用して、LLM駆動のAIエージェントに RBAC（Role-Based Access Control）による権限制御を実装する方法を紹介します。”

PermalinkZenn LLM
Research#llm📝 BlogAnalyzed: Dec 25, 2025 05:01

Let's create a Bitcoin AI Agent using Bitcoin MCP and Strands Agent!

Published:Dec 25, 2025 03:17
1 min read
Zenn AI

Analysis

This article discusses the creation of a Bitcoin AI agent using MCP (Model Context Protocol) and Strands Agent. It highlights the growing importance of MCP, especially after its recent move to the Linux Foundation. The article likely delves into the technical aspects of integrating these technologies to enable AI models to interact with the Bitcoin network. The author anticipates increased usage of MCP in the future, suggesting its potential to revolutionize how AI interacts with blockchain technologies. The article is part of the Model Context Protocol Advent Calendar 2025.

Key Takeaways

Reference

“こんにちは！エンジニアの皆さん、MCP (Model Context Protocol) はもう触っていますか？”

PermalinkZenn AI
Research#llm📝 BlogAnalyzed: Dec 24, 2025 17:16

MCP Implementation: OAuth2/PKCE Authentication and Dynamic Skill Expansion

Published:Dec 24, 2025 14:10
1 min read
Zenn LLM

Analysis

This article discusses the implementation of MCP (Model Context Protocol) and addresses challenges encountered in real-world deployment. It focuses on solutions related to OAuth2/PKCE authentication and dynamic skill expansion. The author aims to share their experiences and provide insights for others working on MCP implementations. The article highlights the importance of standardized protocols for connecting LLMs with external tools and managing context effectively. It also touches upon the difficulties of context management in traditional LLM workflows and how MCP can potentially alleviate these issues. The author's goal is to contribute to the development and adoption of MCP by sharing practical implementation strategies.
Reference

“LLMと外部ツールを標準的なプロトコルで繋ぐというこの技術に、私も大きな期待を持って触れ始めました。”

PermalinkZenn LLM
Research#llm📝 BlogAnalyzed: Dec 24, 2025 13:44

Building a Custom MCP Server for Fishing Information: Understanding MCP

Published:Dec 24, 2025 01:03
1 min read
Zenn LLM

Analysis

This article details the process of building a custom MCP (Model Context Protocol) server to retrieve fishing information, aiming to deepen understanding of MCP. It moves beyond the common weather forecast example by incorporating tidal API data. The article focuses on practical implementation and integration with an MCP client (Claude Desktop). The value lies in its hands-on approach to learning MCP and providing a more unique use case than typical examples. It would benefit from more detail on the specific challenges encountered and solutions implemented during the server development.
Reference

“Model Context Protocol (MCP) is a standard protocol for integrating external data and tools into LLM applications.”

PermalinkZenn LLM
AI#ChatGPT📝 BlogAnalyzed: Dec 24, 2025 14:02

Searching a Portal Site DB with ChatGPT: Introduction to OpenAI Apps SDK x MCP

Published:Dec 23, 2025 10:11
1 min read
Zenn ChatGPT

Analysis

This article discusses using OpenAI's Apps SDK and MCP (Model Context Protocol) to enable ChatGPT to search the database of "Koetecco byGMO," a Japanese portal site for children's programming classes. It highlights the practical application of these tools to create a functional search feature within ChatGPT, allowing users to find relevant programming classes based on specific criteria (e.g., location, subject). The article likely delves into the technical aspects of implementation, showcasing how the SDK and MCP facilitate communication between ChatGPT and the database. The focus is on a real-world use case, demonstrating the potential of AI to enhance search and information retrieval.
Reference

“"Koetecco" is the No. 1 programming class search site for children with the most reviews and listed classrooms, with information on over 14,000 classrooms nationwide.”

PermalinkZenn ChatGPT
Technology#AI Infrastructure📝 BlogAnalyzed: Jan 3, 2026 07:21

Google Announces Cloud API Registry for MCP Server Management

Published:Dec 11, 2025 15:23
1 min read
Publickey

Analysis

Google's Cloud API Registry aims to streamline the discovery, management, and monitoring of MCP servers, crucial for AI agents interacting with external tools. This move suggests Google's continued investment in AI infrastructure and its commitment to providing tools for developers working with generative AI and AI agents.
Reference

“MCP (Model Context Protocol) is generally a protocol used when generative AI and AI agents call external tools to obtain information or operate.”

PermalinkPublickey