How do I install io.github.daedalus/mcp-llm-gateway?

Clone io.github.daedalus/mcp-llm-gateway from https://github.com/daedalus/mcp-llm-gateway and configure it as an MCP server in your client (Claude Desktop, Cursor, or VS Code).

Is io.github.daedalus/mcp-llm-gateway open source?

Yes, io.github.daedalus/mcp-llm-gateway is open source under the MIT license. Source code is available at https://github.com/daedalus/mcp-llm-gateway.

What category does io.github.daedalus/mcp-llm-gateway belong to?

io.github.daedalus/mcp-llm-gateway is listed under Developer Tools MCP servers on MCPFind.

io.github.daedalus/mcp-llm-gateway — MCP Server for Developer Tools

Q: What is io.github.daedalus/mcp-llm-gateway?

MCP-compatible LLM gateway that proxies completion requests.

MCP LLM Gateway

MCP-compatible LLM gateway that proxies completion requests to downstream OpenAI-compatible providers.

mcp-name: io.github.daedalus/mcp-llm-gateway

Install

pip install mcp-llm-gateway

Usage

Configuration

Set the following environment variables:

DOWNSTREAM_URL: Base URL for the OpenAI-compatible downstream API (required)
DEFAULT_MODEL: Default model to use for completions (required)
MODEL_LIST_URL: URL to fetch available models from (optional, defaults to models.dev)
API_KEY: Optional API key for downstream (passthrough)
TIMEOUT: Request timeout in seconds (optional, default: 60)

MCP Server

Run the MCP server with stdio transport:

mcp-llm-gateway

MCP Tools

The server exposes the following tools:

list_models(): List all available models from the remote endpoint
complete(prompt, model, max_tokens, temperature): Send a completion request to the downstream LLM provider

MCP Resources

models://list: Returns the list of available models
config://info: Returns current gateway configuration

Development

git clone https://github.com/daedalus/mcp-llm-gateway.git
cd mcp-llm-gateway
pip install -e ".[test]"

# run tests
pytest

# format
ruff format src/ tests/

# lint
ruff check src/ tests/

# type check
mypy src/

API

core.models

Model: Dataclass representing an available LLM model
CompletionRequest: Dataclass for completion request payloads
GatewayConfig: Dataclass for gateway configuration

adapters.http

HTTPAdapter: HTTP client for downstream API communication
ModelListAdapter: Adapter for fetching model list from remote endpoints

services.gateway

ModelService: Service for managing model discovery and caching
CompletionService: Service for handling completion requests
ConfigService: Service for managing gateway configuration

Set up in your AI client

AI clientOperating system

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json

{
  "mcpServers": {
    "io-github-daedalus-mcp-llm-gateway": {
      "command": "uvx",
      "args": [
        "mcp-llm-gateway"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Compatible MCP Clients

io.github.daedalus/mcp-llm-gateway works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.

Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.

VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.

Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.

Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

io.github.daedalus/mcp-llm-gateway