MCP Security Risks and Mitigations
By My Ultimate Guide For Everything
| May 10, 2025
| mcp, llm, security-risk, prompt-injection, token-theft, server-compromise, rug-pool, tool-shadowing, tool-poisoning, consent-fatigue
Understanding Model Context Protocol (MCP) Security Risks in LLM Systems As large language models (LLMs) evolve to support more powerful and context-aware applications, new paradigms like the Model Context Protocol (MCP) have emerged. MCP offers a structured way to organize the inputs provided to an LLM, typically encompassing task instructions, memory state, tool documentation, user profiles, historical conversation context, and more. While this protocol enhances the power and usability of LLM-driven systems, it also introduces critical security risks that must be mitigated to ensure user safety and system integrity.
Solve Too Many Tokens in Streamlit-Based MCP Servers
By My Ultimate Guide For Everything
| Apr 11, 2025
| mcp, mcp-server, mcp-client, streamlit, fastapi, too-many-tokens, token-limit, context-window, open-ai, claude
Solving “Too Many Tokens” in Streamlit-Based MCP Servers: A Deep Dive When you’re building a Model Context Protocol (MCP) server using Streamlit, you may encounter the notorious error: “Too many tokens”. This occurs when the input passed to a large language model (LLM) exceeds the maximum token limit allowed by the API (e.g., OpenAI’s GPT-4, Claude, etc.). It’s a common bottleneck in systems that continuously build up context over time.
Host MCP Client or Server Using Streamlit
Hosting a Model Context Protocol (MCP) Client or Server with Streamlit As large language models (LLMs) continue to evolve, so too does the need for managing context efficiently and modularly. The Model Context Protocol (MCP) is emerging as a framework for managing, exchanging, and interpreting the context in which a model operates. Whether you’re building applications that use Retrieval-Augmented Generation (RAG), integrating long-term memory, or developing interactive agents, a well-defined MCP architecture can make your system more scalable and interpretable.