MCP-Flowise
Related Servers
Alternatives to MCP-Flowise
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceA Model Context Protocol server that enables LLM tools to create, manage, and run Flowise chatflows and agentflows programmatically.12MIT
- AlicenseNot gradedqualityDmaintenanceA Python implementation of the Model Context Protocol that enables applications to provide standardized context for LLMs, allowing developers to build servers that expose data and functionality to LLM applications.MIT
- AlicenseNot gradedqualityDmaintenanceA Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.MIT
- FlicenseAqualityNot gradedmaintenanceA Model Context Protocol server that allows LLMs to interact with Python environments, enabling code execution, file operations, package management, and development workflows.9-
- AlicenseNot gradedqualityDmaintenanceA FastAPI-based implementation of the Model Context Protocol that enables standardized interaction between AI models and development environments, making it easier for developers to integrate and manage AI tasks.10MIT
- FlicenseNot gradedqualityDmaintenanceA Python-based implementation of the Model Context Protocol that enables communication between a model context management server and client through a request-response architecture.-
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: one lists available chatflows, and the other creates predictions using a specific chatflow. There is no overlap in functionality, and an agent can easily differentiate between them based on their clear descriptions.
Both tools follow a consistent verb_noun naming pattern: list_chatflows and create_prediction. The naming is predictable and readable, with no deviations in style or convention across the tool set.
With only 2 tools, the server feels thin for its apparent domain of interacting with Flowise chatflows. While the tools cover listing and creating predictions, the lack of operations like updating, deleting, or managing chatflows suggests an incomplete surface that may limit agent workflows.
The tool set is severely incomplete for a chatflow management domain. It only provides list and create operations, missing essential CRUD functionality such as updating or deleting chatflows, retrieving specific chatflow details, or handling prediction updates. This will likely cause agent failures in more complex scenarios.