ollama-MCP-server

What is ollama-MCP-server?

The ollama-MCP-server is a Model Context Protocol (MCP) server that facilitates seamless integration between local Ollama LLM instances and MCP-compatible applications, providing advanced task decomposition, evaluation, and workflow management.

How to use ollama-MCP-server?

To use the ollama-MCP-server, install it via pip, configure your environment variables, and run the server. You can then interact with it using various tools to manage tasks and evaluate results.

Key features of ollama-MCP-server?

• Task decomposition for complex problems
• Result evaluation and validation
• Management and execution of Ollama models
• Standardized communication via MCP protocol
• Advanced error handling with detailed messages
• Performance optimizations including connection pooling and LRU caching

Use cases of ollama-MCP-server?

1. Decomposing complex tasks into manageable subtasks.
2. Evaluating task results against specified criteria.
3. Running various Ollama models for different queries.

FAQ from ollama-MCP-server?

• What is the purpose of the ollama-MCP-server?

It serves as a bridge between local LLM instances and applications, enabling efficient task management and evaluation.

• How do I install the server?

You can install it using pip with the command pip install ollama-mcp-server.

• Can I customize the server settings?

Yes, you can adjust settings in the config.py file for performance and model specifications.