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🦅 Saqr-MCP

@ahmedhassan456

Repository

About 🦅 Saqr-MCP

Saqr-MCP is a powerful Python application that implements the Model Context Protocol (MCP) to enable advanced AI assistant capabilities. It supports both local models through Ollama and cloud models through Groq, providing a flexible client-server architecture

Basic information

Category

AI & Agents

License

MIT

Runtime

python

Transports

stdio

Publisher

ahmedhassan456

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "Saqr-MCP": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is 🦅 Saqr-MCP?

🦅 Saqr-MCP is a Python application that implements the Model Context Protocol (MCP) to enable advanced AI assistant capabilities. It supports both local models through Ollama and cloud models through Groq, providing a flexible client-server architecture with tools for web search, memory management, document generation, and advanced reasoning.

How to use 🦅 Saqr-MCP?

Install dependencies with UV, configure environment variables (API keys for Tavily, Groq, Mem0; Ollama model name), and run python main.py. Type queries in the interactive console; use quit to exit. To use Groq instead of Ollama, modify main.py to import from src.groq_client.

Key features of 🦅 Saqr-MCP

  • Interactive chat interface for querying models
  • Support for local models (Ollama) and cloud models (Groq)
  • Advanced web search capabilities using Tavily API
  • Word document generation from markdown content
  • Comprehensive memory management system using mem0
  • Advanced reasoning and thought process tracking

Use cases of 🦅 Saqr-MCP

  • Perform real-time web searches to retrieve up-to-date information
  • Create and manage persistent memories for context-aware interactions
  • Generate formatted Word documents from markdown content
  • Record and analyze reasoning processes during complex problem-solving
  • Switch between local and cloud models depending on availability or cost

FAQ from 🦅 Saqr-MCP

What are the prerequisites for using 🦅 Saqr-MCP?

Python 3.11 or higher, Ollama installed for local model usage, and the UV package manager (recommended).

What API keys are required and where do I get them?

You need a Tavily API key from app.tavily.com, a Groq API key from console.groq.com, and a Mem0 API key from mem0.ai. Configure them in a .env file based on .env.example.

How do I switch between local and cloud models?

By default the app uses Ollama. To use Groq, edit main.py to import SaqrMCPClient from src.groq_client instead of src.ollama_client.

What tools are available on the server?

Tools include web_search, word_file_generator, add_memory, get_all_memories, search_memories, think, get_thoughts, clear_thoughts, and get_thought_stats.

What is the project structure?

The entry point is main.py. The src/ folder contains ollama_client.py, groq_client.py, server.py, and logger.py.

Comments

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