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Provides a suite of test servers implementing the Model Context Protocol (MCP).
Enables interaction with MSSQL databases, facilitating SQL query execution and business intelligence tasks.
Simplifies the integration of Model Context Protocol (MCP) functionality into Elixir-based Phoenix or Bandit servers.
Streamline code snippet organization and clipboard management for developers with tag-based search and AI-assistant integration.
Executes Python code generated by LLMs in a secure, locally-hosted environment, leveraging Hugging Face's LocalPythonExecutor and MCP for LLM application integration.
Enables AI assistants to interact with Atlassian Data Center products (Jira, Confluence, and Bitbucket) through the Model Context Protocol (MCP).
Integrates diverse AI models into Claude Desktop, empowering enhanced development and analytical capabilities.
Enables Claude to execute shell commands securely through the Model Context Protocol.
Connects Model Context Protocol (MCP) clients to Gemini Cloud Assist APIs, enabling natural language management and troubleshooting of Google Cloud environments.
Enables secure execution of shell commands with dynamic approval and audit logging.
Enables applications to provide context to large language models for Algorand blockchain interactions.
Manages todo items within Large Language Models through a comprehensive API.
Connects Bee wearable lifelogging data to AI via the Model Context Protocol.
Enables AI assistants to perform network scanning operations using NMAP through a standardized interface.
Automates browser tasks through an MCP server using DrissionPage and FastMCP, offering browser operation APIs for AI integration.
Enables AI tools to interact with Gradle projects programmatically via the Model Context Protocol.
Connects WhatsApp Web with AI models via the Model Context Protocol (MCP) for automated messaging and contact management.
Enables AI clients to interact with Mailgun services using the Model Context Protocol.
Provides an advanced MCP server for RAG-enabled memory, leveraging a knowledge graph with vector search capabilities.
Enables Large Language Models to interact with cheminformatics functionalities, performing tasks like compound identification, structure conversion, and property calculation.
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