Model Council runs on your own machine — the client starts it, so there is no endpoint to ping. 467 installs a week from pypi. Last commit 24 Aug 2026.
Consult other LLMs as tools — ask them, compare their answers, synthesize a conclusion.
Today is the operative word: we check Model Council every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add model-council -- uvx model-council-mcp
{
"mcpServers": {
"model-council": {
"args": [
"model-council-mcp"
],
"command": "uvx"
}
}
}
[mcp_servers.model-council]
command = "uvx"
args = ["model-council-mcp"]
{
"mcpServers": {
"model-council": {
"args": [
"model-council-mcp"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"model-council": {
"args": [
"model-council-mcp"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
COUNCIL_MODELS (Comma-separated short ids for the models to seat, e.g. 'gpt5,glm'. Each id then takes its own <ID>_BASE_URL, <ID>_API_KEY, <ID>_MODEL and optional <ID>_FORMAT (openai or anthropic). Omit to use a config file instead.), COUNCIL_CONFIG (Path to a JSON config file, for rosters large enough that several models share one endpoint. Defaults to ~/.config/model-council/config.json when that exists.).
The author declared them in the registry entry; get the values from the project itself.
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