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Enables browser automation capabilities using Playwright for LLMs to interact with web pages.
Connect Flutter applications with AI coding assistants via the Model Context Protocol.
Enables interaction with Elasticsearch clusters using natural language commands through a Model Context Protocol (MCP) server.
Manage and interact with databases directly within VS Code, combining the power of databases with the convenience of a code editor.
Analyzes code using tree-sitter to provide context-aware code understanding for AI assistants.
Enables AI assistants to augment their responses with context from documentation through vector search and retrieval.
Provides accurate Rust code suggestions for AI assistants by fetching current crate documentation and using LLMs to provide context.
A collection of guides, utilities, clients, and servers developed while exploring and implementing the Model Context Protocol (MCP).
Exposes any web application with an OpenAPI specification as a Model Context Protocol (MCP) server.
Simplify third-party API integrations with an open-source API gateway.
Enhances Claude's ability to solve complex programming tasks by enabling structured, step-by-step reasoning.
Implements the Model Control Panel (MCP) protocol to interact with Apache Doris databases, enabling tasks like query execution and metadata management.
Exposes GraphQL operations as Model Context Protocol (MCP) tools.
Orchestrates access to OpenAI, Google Gemini, and Azure AI models through a unified Model Context Protocol (MCP) interface for enhanced coding workflows.
Enables secure command-line interactions on Windows systems for controlled access to various shells and remote systems via the Model Context Protocol.
Provides AI coding agents with symbol-aware semantic search for precise context on large codebases.
Empower developers to rapidly prototype, develop, and deploy scalable AI-powered applications, including workflows and agents, using a unified TypeScript stack.
Unify code indexing, hybrid search, and LLM decoding into a plug-and-play retrieval stack for rapidly deploying context-aware AI agents.
Enables Large Language Models to query a unified database of security detection rules from various formats.
Integrates AI bots into various messaging platforms and desktop clients, providing extensive local system access and intelligent conversational capabilities through a single, lightweight binary.
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