What should I test first with TKEN?

Start with the TKEN /v1 base URL, run GET /v1/models, choose a returned model ID, then send one small non-streaming /chat/completions request before adding SDKs, UI tools, proxies, CI, or agents.

Should I start with every tool at once?

No. Pick one workflow, prove model discovery and one chat request, save redacted evidence, then expand to SDKs, Open WebUI, LiteLLM, coding tools, CI, or agent hosts.

Which path is safest for an existing OpenAI SDK app?

Run the no-network OpenAI SDK base URL quickcheck first, then run /v1/models and one non-streaming chat request before changing production SDK traffic.

How should MCP or agent hosts be rolled out?

Treat model gateway setup and MCP tool permissions as separate rollouts. Validate TKEN as a model gateway first, then enable one low-risk host or tool permission at a time with spend caps and redacted logs.

Is TKEN affiliated with OpenAI or tool vendors?

No. TKEN is an independent third-party OpenAI-compatible API gateway and is not officially affiliated with OpenAI, model providers, Open WebUI, LiteLLM, Cursor, Continue, or other third-party tools.

Integration decision map

Choose the first TKEN integration path before wiring every tool

TKEN is an OpenAI-compatible multi-model API gateway for developers. Use this map to choose a first safe path for API clients, SDK apps, Open WebUI, LiteLLM, coding tools, CI, or MCP hosts before routing production traffic.

Get API key Open GitHub map

Default rollout sequence smallest useful proof

base_url = "https://www.tken.shop/v1"

1. Run GET /v1/models
2. Choose a returned model ID
3. Send one non-streaming chat request
4. Save redacted status and latency evidence
5. Add one SDK, UI tool, proxy, CI job, or MCP host

Pick one workflow before broad rollout

Prove /v1/models before selecting a model

Keep agent and MCP permissions separate from gateway setup

5-Minute Path Picker

Start with the path that matches the current job. The goal is not to configure every integration surface at once. The goal is to prove one endpoint, one model, one request shape, and one sanitized evidence trail before expanding.

No-code endpoint check

Postman and Bruno API-client smoke tests

Existing SDK app

OpenAI SDK base URL quickcheck

Framework app

Vercel AI SDK and LangChain

Team chat UI

Open WebUI, LiteLLM, Cursor, Continue

Agent or MCP host

MCP host gateway config review

CI confidence

Smoke evidence runner

Default rollout sequence

1. Confirm the OpenAI-compatible base URL

The TKEN base URL is https://www.tken.shop/v1. Keep this value separate from direct-provider configuration so a test does not accidentally hit a different account or endpoint.

2. Run model discovery

Call GET /v1/models before choosing a model. Treat model IDs as route and account specific, not as names you can safely copy from another provider setup.

3. Send one non-streaming chat request

Use a small, non-sensitive prompt and one selected model ID. Delay streaming, tools, JSON mode, embeddings, long-context tests, and agent loops until the basic request is proven.

4. Capture redacted smoke evidence

Save status code, elapsed milliseconds, model count, selected model, and failure class. Do not save API keys, bearer tokens, account IDs, IP addresses, private prompts, or full response text.

5. Add one integration surface

Move one SDK call, one Open WebUI admin proof, one LiteLLM route, one coding-tool key, one CI job, or one read-only MCP host before enabling broader traffic.

Risk signals

Pause and narrow the rollout when a basic check fails. Most early failures are endpoint, key, model ID, request-shape, quota, timeout, or capability mismatch issues. Isolate that class before debugging the surrounding app.

/models fails

Fix base URL and auth before chat tests

Chat fails after /models

Use a returned model ID and simple request

Streaming fails

Keep non-streaming until SSE is proven

Tools fail

Test selected model capability separately

Users differ from admin

Check key scope, route, and proxy layer

Agent cost spikes

Disable loops and add spend caps first

Integration decision map FAQ

Why use a decision map before SDK migration?

It keeps the first proof small. A direct API-client smoke test, SDK base URL check, UI-tool setup, CI job, and MCP host rollout all have different failure modes, so they should not be debugged in one change.

Where is the GitHub guide?

The v0.25.0 examples release includes the integration decision map and links to the related TKEN guides. Open the v0.25.0 release.

What evidence is safe to keep?

Keep endpoint path, HTTP status, elapsed milliseconds, model count, selected model ID, tool or SDK version, and a failure class. Avoid secrets, customer data, full prompts, full outputs, dashboards, billing screens, and private account details.

Does this page claim affiliation with OpenAI or tools?

No. TKEN is an independent third-party OpenAI-compatible API gateway and is not officially affiliated with OpenAI, Anthropic, DeepSeek, MiniMax, Alibaba, Google, xAI, Open WebUI, LiteLLM, Cursor, Continue, Vercel, LangChain, LlamaIndex, Postman, Bruno, or other providers and tools.

TKEN is an independent third-party OpenAI-compatible API gateway. Model availability, pricing, context limits, streaming behavior, tool support, and rate limits can vary by account, channel, and provider status. Live /pricing remains the source of truth.

Pick one first path, then expand

Create a key, use https://www.tken.shop/v1, run model discovery, complete one non-streaming chat request, and only then add the SDK, UI tool, proxy, CI, or MCP host you actually need.

Create account Read guide