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OpenAI-Compatible Provider

Claude-mem can run observation extraction against any endpoint that speaks the OpenAI /chat/completions shape. Set CLAUDE_MEM_PROVIDER to openai-compatible, pick a preset (or supply a base URL), and memory runs entirely off your Claude plan.
claude-mem observer: choosing the claude-mem observer during npx claude-mem install runs memory off-plan with nothing to configure. This page is for bringing your own endpoint and key.

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Why this is separate from the OpenRouter provider

CLAUDE_MEM_OPENROUTER_BASE_URL already lets the OpenRouter client talk to any OpenAI-compatible endpoint, and it keeps working — nothing on that path changed. But it carries three things that belong to openrouter.ai specifically:
  • Attribution headers. HTTP-Referer and X-Title are sent to whatever host the base URL names, so pointing it at NVIDIA announces claude-mem’s OpenRouter identity to NVIDIA.
  • usage: { include: true }, gated on the URL containing openrouter.ai.
  • The cmem.ai gateway’s credential-pinning rules, which decide when a persisted base URL pins a persisted key. Those rules exist so an account-delivered gateway credential is never sent somewhere else — correct, and irrelevant to an endpoint you configured yourself, but you still share the same three settings keys with them.
This provider has its own settings keys and sends a deliberately plain request body: model, messages, temperature, max_tokens, and nothing else. Strict servers (vLLM in particular) reject unknown fields. max_tokens is CLAUDE_MEM_OBSERVER_MAX_OUTPUT_TOKENS (4096 by default); a model that only accepts max_completion_tokens gets the request again with that field. A claude-mem observer key (cm_pro_…) is never sent to these endpoints. Use the key the endpoint issued.

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Quick start: NVIDIA NIM

1

Get a key

Sign in at build.nvidia.com and create an API key. It starts with nvapi-. NVIDIA’s hosted models are free to start, which suits observation extraction: it is high-volume and structured, and does not need a frontier model.
2

Point claude-mem at it

Or keep the key out of settings.json and put it in ~/.claude-mem/.env:
3

Pick a model (optional)

The preset defaults to a small, fast NVIDIA-served model. Any model id from build.nvidia.com works and is passed verbatim:
4

Restart the worker

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Presets

A preset only supplies a default base URL and a default model. Anything it sets is overridden by the matching setting, so switching preset never moves an endpoint or model you pinned yourself.
Local presets need a model id — claude-mem cannot guess which model you loaded. Set CLAUDE_MEM_OPENAI_COMPAT_MODEL to whatever ollama list (or your server) reports, or the provider reports itself unconfigured and dispatch falls through to Claude.

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OpenCode Go and Zen

An OpenCode Go subscription or Zen key works here. opencode-go defaults to kimi-k3; opencode-zen ships no default, so set the model too. Pick ids from https://opencode.ai/zen/go/v1/models or https://opencode.ai/zen/v1/models. Only models served on /chat/completions work.

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Settings

An unknown preset id degrades to custom rather than failing, because settings are read during status polling and a typo should not crash a poll. The viewer’s Settings → Advanced panel edits the provider, preset, base URL and model. The API key is set in ~/.claude-mem/settings.json or ~/.claude-mem/.env only, never through the viewer.

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MiniMax

minimax is MiniMax’s global endpoint and minimax-cn the mainland-China one; use the preset that matches where your account lives. Both default to MiniMax-M3. Any model id MiniMax serves is passed verbatim:
Reasoning models such as the M2 family can open their reply with a <think>…</think> block. claude-mem removes a leading block like that on every preset (it also covers DeepSeek R1 or Qwen3 on Ollama and vLLM), so the reasoning is never stored or re-sent with the next request.

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Any other endpoint

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When a key is required

Setting CLAUDE_MEM_OPENAI_COMPAT_BASE_URL replaces the preset’s endpoint, so whether a key is needed is decided by the endpoint you pointed at, not by the preset name you started from: Without an override, the preset decides — the hosted presets need a key, the local ones do not. A remote endpoint that genuinely needs no authentication still works: set CLAUDE_MEM_OPENAI_COMPAT_API_KEY to any non-empty value. The default errs toward asking for a key because the alternative is a provider that reports itself ready and then fails every observation with a 401.

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OrcaRouter

OrcaRouter serves provider-scoped model ids, such as openai/gpt-4o-mini (the preset’s default) or anthropic/claude-haiku-4.5, behind one sk-orca- key. Its model list is public at https://api.orcarouter.ai/v1/models.

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Troubleshooting

Memory silently runs on Claude instead. Dispatch falls through to Claude when the provider is selected but not fully configured — a missing base URL, a missing model, or a missing key on a preset that needs one. That fall-through is deliberate: a half-configured endpoint should not fail every observation. Check npx claude-mem doctor. 404 from the endpoint. Almost always a wrong base URL or a model the endpoint does not serve; the error names both settings. Note that some gateways prefix model ids differently from the vendor’s own docs. Repeated timeouts. Each request has a deadline of CLAUDE_MEM_LLM_TIMEOUT_MS (180 seconds by default), which a large model on a slow endpoint can still exceed. Raise it, or prefer a small, fast model: observation extraction is a high-volume structured task, not a reasoning benchmark. Empty or cut-off observations. A model that will not hold to the output schema produces nothing usable. Small instruct-tuned models generally do better here than reasoning models, whose thinking output tends to crowd out the structured reply. When the log says a reply was cut off at the output-token limit, raise CLAUDE_MEM_OBSERVER_MAX_OUTPUT_TOKENS.