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Register multiple AI endpoints and auto-route models by capability.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ai-mcp-server" yet — see the docs or source repo.
Help me configure ai-mcp-server to unify chat, vision, embedding, and speech models, and list the available endpoints for each capability.
A multi-model integration setup with discoverable endpoints grouped by chat, vision, embedding, speech, and other capabilities.
I need the agent to automatically choose models by task type: reasoning tasks use reasoning models, image understanding uses vision models, and vectorization uses embedding models. Give me an example routing strategy.
An example routing policy that maps task capabilities to the right model endpoints for automatic agent selection.
List the capabilities supported by the models currently registered in ai-mcp-server, including chat, vision, reasoning, embedding, image generation, TTS, STT, and rerank, and note suitable use cases.
A capability inventory of registered models with typical use cases for each supported capability.
Connect to the mcp API via MCP to extend AI tool capabilities.
Access multiple AI providers in one terminal for generation, search, and comparison.
Connect MCP-capable agents to A2A endpoints for agent-to-agent messaging.
Build, debug, and manage software tasks with natural language across LLMs.
Create, manage, and compose AI agents for MCP-compatible clients and tools.
Turn existing APIs and databases into MCP tools for direct AI use.