FlowLLM MCP Service

Example Use Cases

• 1

  Integrate large language models and embedding services via MCP or HTTP protocols.

• 2

  Build complex workflows combining multiple operations with flexible orchestration.

• 3

  Automatic generation of RESTful APIs and MCP tools for seamless client integration.

Description

FlowLLM simplifies the development of LLM-based HTTP and MCP services by offering easy Op development, flexible flow orchestration, and automatic service generation. It supports building AI assistants, RAG applications, and workflow services that can be integrated into MCP-compatible clients. The platform includes built-in token counting, prompt management, and supports multiple backends for LLM and embedding models, enhancing development efficiency and service scalability.