LiteLLM
This LiteLLM MCP server integrates the LiteLLM library to provide a standardized interface for AI assistants to interact with OpenAI language models. Built using Python and leveraging libraries like Pydantic and FastAPI, it abstracts the complexities of the OpenAI API, handling authentication, request formatting, and response parsing. The server offers text completion capabilities with customizable parameters, enabling AI systems to generate human-like text across various applications. It's designed for developers and researchers who need flexible access to state-of-the-art language models, facilitating use cases such as chatbots, content generation, and natural language processing tasks. The implementation's focus on LiteLLM allows for potential future expansion to support additional model providers beyond OpenAI.
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 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · 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/opencnid/mcp-server-litellm
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve LiteLLM 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.