A reliability-focused AI agent framework utilizing the Model Context Protocol, offering integration with diverse tools and a secure runtime for MCP servers.
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LangChain MCP server provides an agent-ready framework for building MCP servers, allowing AI agents to dynamically access knowledge bases and structured data via composable chains and adapters. It is highly extensible for autonomous workflows.
oatpp-mcp implements Anthropic's Model Context Protocol for the Oat++ C++ framework, enabling comprehensive server integration.
A lightweight, modular MCP-compatible memory and agent protocol server designed for privacy-first, on-device AI agents. Supports local and cloud-based LLMs with persistent, session-aware memory. Also integrates real-time, up-to-date documentation directly into your coding environment, providing accurate and context-aware API information to streamline development workflows and reduce errors.
Extends the Goose AI assistant with a suite of MCP servers, enabling integration with Plex Media Server, Rotten Tomatoes, eBay, SearxNG for web search, and Taskwarrior.
An open-source, modular MCP-aligned server/framework for building custom memory agents with hybrid vector and symbolic memory. Ideal for developers seeking full control over their MCP server setup and agent logic.
sakura-mcp is a Scala-based MCP Framework for building effective agents, featuring comprehensive server and client implementation.
Upsonic is a framework designed for building reliable AI agent applications. It uses the Model Context Protocol (MCP) to support integration with a wide range of tools and provides a secure runtime environment for MCP servers.
AI Integration (MCP Servers)
ai-agent, framework, secure, integration
No pricing information provided.