Outsource MCP

Outsource MCP is a Model Context Protocol server designed to give AI applications a single, consistent interface for calling on the power of dozens of external model providers. By abstracting away provider‑specific APIs, developers can write once and run anywhere—whether they are using Claude Desktop, Cline, or any other MCP‑enabled client. The server’s core value lies in eliminating the friction of managing multiple authentication keys, SDKs, and request formats while still giving users access to a broad portfolio of models.

At its heart, the server exposes two high‑level tools: and . The text tool accepts a provider name, model identifier, and prompt, then delegates the request to an Agno agent that talks directly to the chosen provider. Image generation is similarly routed, currently limited to OpenAI’s DALL‑E 2 and DALL‑E 3 but structured so additional image models can be added later. This simple three‑parameter API keeps client code lean and readable, allowing developers to focus on prompt engineering rather than plumbing.

Key capabilities include:

• Multi‑provider support: Over 20 AI services—from OpenAI, Anthropic, and Google to niche players like DeepSeek and Cerebras—are reachable through the same interface.
• Unified authentication: Only the API keys you need are set as environment variables; unused providers simply remain dormant.
• Rapid prototyping: Because the server is built on FastMCP, it starts quickly and scales with minimal overhead.
• Extensibility: The Agno agent framework makes it straightforward to add new providers or customize prompt handling without touching the MCP layer.

Typical use cases span rapid experimentation, where a data scientist can flip between GPT‑4o and Claude‑3.5 to compare outputs, to production pipelines that need a fallback strategy—if one provider throttles or fails, the system can automatically switch to another. In creative workflows, designers can request DALL‑E images on demand while simultaneously generating descriptive captions with a text model. For customer support bots, the server can route queries to the most cost‑effective or latency‑optimal provider at runtime.

Because MCP clients already handle context and token limits, integrating Outsource MCP simply involves adding a new server entry in the client’s configuration. Once configured, any MCP‑enabled tool can invoke or , and the server will transparently translate those calls into provider‑specific requests. This tight integration preserves the natural conversational flow that developers expect from AI assistants while unlocking a diverse ecosystem of models behind a single, clean API.