mcp-computeflux
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Alternatives to mcp-computeflux
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Related Servers
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to discover and inspect available open models, estimate token costs, and run chat completions through an OpenAI-compatible inference endpoint, with optional bearer-key authentication for billed calls.Apache 2.0
- AlicenseAqualityAmaintenanceExposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.5107 PyPIMIT
- FlicenseNot gradedqualityDmaintenanceA local MCP server exposing the OpenAI platform REST API as tools for file management, fine-tuning, inference, images, audio, batch processing, and organization usage/costs.-
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients to manage and run local or cloud LLMs, generate completions and embeddings, and perform web search/fetch through exposed tools.958 npmAGPL 3.0
- AlicenseAqualityBmaintenanceEnables listing models and running non-streaming chat completions against RelayRouter's OpenAI-compatible API, so agents can discover available models and send chat requests through a key-configured MCP endpoint.2MIT
- AlicenseNot gradedqualityCmaintenanceExposes local LM Studio language models as MCP tools, enabling chat completions and model listing through a local OpenAI-compatible API without requiring API keys.MIT
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: listing available models versus sending a chat completion request. There is no overlap in functionality or ambiguous selection risk.
Both tools share the same 'computeflux_' prefix and use snake_case, which is consistent. The only minor deviation is that one name is a plural noun and the other is a verb-like action, but the pattern remains readable.
Two tools is slightly under the typical 3–15 range, but for a narrow OpenAI-compatible wrapper covering model listing and chat completions, each tool earns its place. The surface is minimal but reasonable for the stated purpose.
Core chat functionality and model listing are present, but an OpenAI-compatible endpoint often includes other common operations such as embeddings, completions, or audio. These gaps are notable, though agents could still perform basic chat workflows.