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mcp-server-llmling

by phil65

mcp-server-llmling is a server for the Machine Chat Protocol (MCP) that provides a YAML-based configuration system for LLM applications. It allows to set up custom MCP servers serving content defined in YAML files.

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What is mcp-server-llmling?

mcp-server-llmling is a server for the Machine Chat Protocol (MCP) that leverages LLMLing to provide a YAML-based configuration system for LLM applications. It enables the creation of custom MCP servers that serve content defined in YAML files, allowing for static declaration of LLM environments without requiring code.

How to use mcp-server-llmling?

The server can be used with Zed Editor, Claude Desktop, or manually from the command line. Configuration is done through a YAML file that defines resources, tools, toolsets, and prompts. The server implements the MCP protocol for resource, tool, and prompt operations.

Key features of mcp-server-llmling

  • Resource Management (Text files, Raw text, CLI output, Python code, Images)

  • Tool System (Python functions, OpenAPI-based tools)

  • Prompt Management (Static, Dynamic, File-based prompts)

  • Multiple Transport Options (Stdio, SSE, Custom implementations)

Use cases of mcp-server-llmling

  • Creating custom LLM environments

  • Integrating LLMs with existing tools and data sources

  • Standardizing LLM interactions using the MCP protocol

  • Developing LLM-powered applications with YAML configuration

FAQ from mcp-server-llmling

What is MCP?

MCP stands for Machine Chat Protocol, a standardized protocol for LLM interaction.

How do I configure resources?

Resources are configured in the YAML file under the 'resources' section, specifying the type and path/content.

Can I use custom Python functions as tools?

Yes, you can register and execute Python functions as LLM tools by defining them in the 'tools' section of the YAML file.

What transport options are available?

The server supports Stdio-based communication (default), Server-Sent Events (SSE) for web clients, and custom transport implementations.

How do I start the server?

The server can be started from the command line using uvx mcp-server-llmling@latest or programmatically using the LLMLingServer class in Python.