Claude Desktop
This page was last updated and tested on 2026-06-03. The setup is stable, but Claude Desktop updates can change UI labels or configuration keys without notice — if something stops working, check this page for an updated guide.
Claude Desktop ships with a Cowork agent harness — skills, plugins, MCP servers, and multi-agent coordination — that can be pointed at any Anthropic-compatible endpoint, including your private-gpt server. This lets you run the full Cowork experience against your self-hosted models without routing data through Anthropic’s first-party infrastructure.
For the official Anthropic documentation on third-party inference, see Claude Desktop third-party inference.
Compatibility
Tested against private-gpt on 2026-05-27.
Prerequisites
- Claude Desktop installed and up to date
- Developer mode enabled: Help → Troubleshooting → Enable Developer Mode
private-gptserver running (see serve)
The Configure Third-Party Inference option lives under Menu → Developer. If it is missing, update Claude Desktop and restart with developer mode enabled. Users on corporate or Team plans may not see it — it may be plan-gated.
Setup
Open the third-party inference panel
In Claude Desktop: Menu → Developer → Configure Third-Party Inference
Set the gateway values
private-gpt exposes an Anthropic-compatible API, so no adapter or proxy is needed. If root_path is empty, omit the trailing path:
Configure your model
Open the model configuration panel and add a custom model entry with the following values:
Claude Desktop requires the Model ID to follow the claude-* naming convention (e.g. claude-local, claude-private). Using an ID that does not start with claude- will cause the model to be rejected or ignored.
Do not include gpt anywhere in the Model ID — Claude Desktop bans that string and will reject the model entry.
Because Claude Desktop requires a claude-* Model ID, the value you enter (e.g. claude-local) will not match any model name in your settings.yaml — PrivateGPT will automatically fall back to the default model configured on the server.
For fine-grained control over context window, tokenizer, tool support, and sampling parameters, see Advanced Model Configuration.

