MCP
Building Advanced MCP (Model Context Protocol) Agents with Multi-Agent Coordination, Context Awareness, and Gemini Integration
class MCPAgent: “””Advanced MCP Agent with evolved capabilities – Jupyter Compatible””” def __init__(self, agent_id: str, role: AgentRole, api_key: str = None): self.agent_id = agent_id self.role = role self.api_key = api_key self.memory = [] self.context = AgentContext( agent_id=agent_id, role=role, capabilities=self._init_capabilities(), memory=[], tools=self._init_tools() ) self.model = None if GEMINI_AVAILABLE and api_key: try: genai.configure(api_key=api_key) self.model = genai.GenerativeModel(‘gemini-pro’) print(f”✅…
Developers lose focus 1,200 times a day — how MCP could change that
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Software developers spend most of their time not writing code; recent industry research found that actual coding accounts for as little as 16% of developers’ working hours, with the…
Is Model Context Protocol MCP the Missing Standard in AI Infrastructure?
The explosive growth of artificial intelligence, particularly large language models (LLMs), has revolutionized how businesses operate, from automating customer service to enhancing data analysis. Yet, as enterprises integrate AI into core workflows, a persistent challenge emerges: how to securely and efficiently connect these models to real-world data sources without custom, fragmented integrations. Introduced by Anthropic…
Model Context Protocol (MCP) FAQs: Everything You Need to Know in 2025
The Model Context Protocol (MCP) has rapidly become a foundational standard for connecting large language models (LLMs) and other AI applications with the systems and data they need to be genuinely useful. In 2025, MCP is widely adopted, reshaping how enterprises, developers, and end-users experience AI-powered automation, knowledge retrieval, and real-time decision making. Below is…
5 key questions your developers should be asking about MCP
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now The Model Context Protocol (MCP) has become one of the most talked-about developments in AI integration since its introduction by Anthropic in late 2024. If you’re tuned into the…
Model Context Protocol (MCP) for Enterprises: Secure Integration with AWS, Azure, and Google Cloud- 2025 Update
The Model Context Protocol (MCP), open-sourced by Anthropic in November 2024, has rapidly become the cross-cloud standard for connecting AI agents to tools, services, and data across the enterprise landscape. Since its release, major cloud vendors and leading AI providers have shipped first-party MCP integrations, and independent platforms are quickly expanding the…
Spritle’s Plugin-First MCP Architecture: The Hidden Tech Behind Fast AI Rollouts
Introduction In the fast-moving world of AI, time-to-market can be the difference between industry leadership and playing catch-up. For business owners and product leaders, the promise of AI is no longer just theoretical — it’s operational. But behind every smooth AI rollout lies an often-overlooked secret: architectural design. At Spritle, we’ve engineered that edge with…
How MCP Agents Help SaaS Security Teams Automate SOC 2 & HIPAA
Introduction Security and compliance teams at fast-growing SaaS companies are under constant pressure. Whether it’s a SOC 2 audit, HIPAA documentation, or staying updated with GDPR regulations, the compliance burden keeps growing—while the margin for error keeps shrinking. Despite having robust DevSecOps practices and cloud security tools in place, many teams still rely on spreadsheets,…
A Step-by-Step Coding Guide to Defining Custom Model Context Protocol (MCP) Server and Client Tools with FastMCP and Integrating Them into Google Gemini 2.0’s Function‑Calling Workflow
In this Colab‑ready tutorial, we demonstrate how to integrate Google’s Gemini 2.0 generative AI with an in‑process Model Context Protocol (MCP) server, using FastMCP. Starting with an interactive getpass prompt to capture your GEMINI_API_KEY securely, we install and configure all necessary dependencies: the google‑genai Python client for calling the Gemini API, fastmcp for defining and…