A Python client for temporal reasoning and learning using Model Context Protocol (MCP) servers
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# Temprl MCP Client A flexible Python library and CLI tool for interacting with Model Context Protocol (MCP) servers using any LLM model. ## Overview Temprl MCP Client is both a Python library and a command-line tool that allows you to query and interact with MCP servers through natural language. It connects to any number of configured MCP servers, makes their tools available to language models (OpenAI, Anthropic, Ollama, LMStudio), and provides a conversational interface for accessing and manipulating data from these servers. The project demonstrates how to: - Connect to multiple MCP servers simultaneously - List and call tools provided by these servers - Use function calling capabilities to interact with external data sources - Process and present results in a user-friendly way - Create a reusable Python library with a clean API - Build a command-line interface on top of the library ## Features - **Multiple Provider Support**: Works with OpenAI, Anthropic, Ollama, and LMStudio models - **Modular Architecture**: Clean separation of concerns with provider-specific modules - **Dual Interface**: Use as a Python library or command-line tool - **MCP Server Integration**: Connect to any number of MCP servers simultaneously - **Tool Discovery**: Automatically discover and use tools provided by MCP servers - **Flexible Configuration**: Configure models and servers through JSON configuration - **Environment Variable Support**: Securely store API keys in environment variables - **Comprehensive Documentation**: Detailed usage examples and API documentation - **Installable Package**: Easy installation via pip with `temprl-mcp-client` command ## Prerequisites Before installing Temprl MCP Client, ensure you have the following prerequisites installed: 1. **Python 3.8+** 2. **SQLite** - A lightweight database used by the demo 3. **uv/uvx** - A fast Python package installer and resolver ### Setting up Prerequisites #### Windows …
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