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Enables Large Language Models (LLMs) to securely interact with the blockchain through MetaMask, safeguarding private keys from AI agents.
Provides a TypeScript-based playground for experimenting with and extending an Model Context Protocol server.
Connects AI assistants to Buildable projects for contextual understanding, task management, and real-time collaboration.
Analyzes codebases and builds a comprehensive graph database using Neo4j to enable AI-powered code understanding and assistance.
Captures screenshots of web pages at multiple breakpoints and reports JavaScript errors, console logs, and network issues.
Enables a self-hosted AI environment on Windows, integrating Ollama, Open WebUI, and MCP for local language model management and chat interaction.
Provides access to a MySQL database, allowing agents to execute SQL queries.
Demonstrates how to set up a Model Context Protocol (MCP) server and client using Server-Sent Events (SSE) for LLM prompting.
Automates interactions with Slack channels using Spring AI.
Enables LLMs to search, retrieve, and get random photos from Unsplash's extensive collection.
Enables AI assistants to interact with Apache Solr for search, indexing, and management tasks.
Provides an MCP server implementation in Elixir.
Enables integration between KoboldAI's text generation and applications compatible with the Model Context Protocol (MCP).
Exposes PubNub SDK documentation and API resources to LLM-powered tools, enhancing AI agent interaction with PubNub.
Manages and interacts with the Flowcore Platform via the Model Context Protocol (MCP).
Provides Git operations through the Model Context Protocol (MCP).
Enables AI assistants and external tools to leverage Visual Studio Code's Language Server Protocol (LSP) features for advanced code intelligence via the Model Context Protocol (MCP).
Streamlines development workflows by providing consistent environments, tooling configurations, and coding patterns for modern AI Agentic coding across multiple repositories.
Provides long-term memory storage for LLMs, enabling them to retain context across multiple sessions by leveraging semantic search and embeddings.
Enables integration with Zendesk to manage and interact with tickets programmatically.
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