Multi-LLM API Gateway
This MCP server implementation enables AI assistants to interact with multiple language model APIs through a unified interface. Built with Python using FastAPI, it supports both OpenAI and Anthropic models, allowing seamless switching between different AI providers. The server handles API authentication, request formatting, and streaming responses, while the accompanying client script provides a simple way to connect to the server. This implementation is particularly useful for developers who need to work with multiple AI models or want to create applications that can easily switch between different AI services without changing their core integration code.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/freedanfan/mcp_server
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Multi-LLM API Gateway from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.