How do I configure the LLM model?
Use the `LLM_MODEL` environment variable or the `--model` CLI argument. Default is `qwen2.5-coder:latest`.
@VyacheslavVanin
Basic information
Local http server that proxies requests o LLMs and uses mcp-servers if needed
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-http-host": {
"command": "uv",
"args": [
"run",
"main.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
It is a FastAPI server for chat interactions with LLMs, using OpenAI-compatible providers. It is configured via environment variables and CLI arguments, and supports tool approval workflows.
Configure via environment variables (e.g., LLM_API_KEY, LLM_MODEL) or CLI arguments (e.g., --model, --port). Start the server using uv run main.py with desired options. Send requests to endpoints like POST /user_request and POST /approve.
Use the `LLM_MODEL` environment variable or the `--model` CLI argument. Default is `qwen2.5-coder:latest`.
Set the `LLM_API_KEY` environment variable or use the `--api-key-file` CLI argument pointing to a file with the key.
Only `openai` provider is supported, but the base URL can be changed (default OpenRouter).
Send a POST request to `/approve` with `request_id` and `approve` boolean in the JSON body.
If `--debug-messages` is enabled, logs are written to `/tmp/llm-requester.messages.log`.

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