Best Context Engineering Tools for Model Context Protocol (MCP)

Compare the Top Context Engineering Tools that integrate with Model Context Protocol (MCP) as of September 2025

This a list of Context Engineering tools that integrate with Model Context Protocol (MCP). Use the filters on the left to add additional filters for products that have integrations with Model Context Protocol (MCP). View the products that work with Model Context Protocol (MCP) in the table below.

What are Context Engineering Tools for Model Context Protocol (MCP)?

Context engineering tools are specialized frameworks and technologies that manage the information environment surrounding large language models (LLMs) to enhance their performance in complex tasks. Unlike traditional prompt engineering, which focuses on crafting individual inputs, context engineering involves dynamically assembling and structuring relevant data—such as user history, external documents, and real-time inputs—to ensure accurate and coherent outputs. This approach is foundational in building agentic AI systems, enabling them to perform multi-step reasoning, maintain state across interactions, and integrate external tools or APIs seamlessly. By orchestrating the flow of information and memory, context engineering tools help mitigate issues like hallucinations and ensure that AI systems deliver consistent, reliable, and context-aware responses. Compare and read user reviews of the best Context Engineering tools for Model Context Protocol (MCP) currently available using the table below. This list is updated regularly.

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    Agent Payments Protocol (AP2)
    Google’s Agent Payments Protocol (AP2) is an open protocol designed together with over 60 payments, fintech, and tech companies (e.g., Mastercard, PayPal, Adyen, Coinbase, Etsy) to enable secure, agent-led transactions across platforms. It builds on earlier open standards like Agent2Agent (A2A) and the Model Context Protocol (MCP) to ensure that when an AI agent initiates or completes a payment on behalf of a user, three core requirements are met: authorization (proving the user explicitly gave permission for that specific purchase), authenticity (ensuring the agent’s intended purchase matches what the user meant), and accountability (clear audit trails and responsibility in case of errors or fraud). The protocol uses mandates, which are cryptographically signed digital contracts backed by verifiable credentials.
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