One endpoint. Every model. Your agents.
If your code already speaks to OpenAI, it already speaks to us. Change the base URL and the model string — the SDK, the request shape and the streaming format stay exactly as they are.
One endpoint
Your SDK, your request shape, your streaming parser. One base URL in front of every provider we route to.
Every model
300+ models from 50+ providers behind one string. Change the model without changing anything else.
Your agents
When one request is not enough: runs that call tools, work in a sandbox, and come back on a schedule.
What it does
Chat completions and responses
Both API shapes, streaming or buffered, with the same payloads you already send.
Tools and structured output
Function calling and JSON-shaped responses across every model that supports them.
MCP
Connect Model Context Protocol servers and let a model use your own tools.
Media
Image and video generation, speech synthesis and transcription, through the same key.
Retrieval
Embeddings and reranking, for search and RAG.
Web search
Grounded answers without wiring up a search provider yourself.
Agents, not just requests
The difference between a call and a colleague is that one of them comes back round. The same key runs both.
Runs that outlive the connection
A run writes as it goes and does not stop when the socket does. Close the tab and reattach by id; you lose the view, not the work.
Tools, yours included
Platform tools plus any MCP server you bring. Writes can be held at an approval gate instead of just happening.
A real sandbox
A container with a filesystem and a shell, so a run can write files, execute code and hand back what it produced.
Schedules
Run on a cron rather than on a request. Ours have been running hourly since we built it.
What you get around it
The parts that are not the model call, and usually take longer to build.
Per-key analytics
Spend, latency and error rate per API key, per model, in the dashboard.
One bill
Credit that works across every provider. No separate contracts, no twenty invoices.
Published data policies
For each provider serving a model, whether it trains on prompts, stores them, or keeps nothing — on the model's own page.
Model catalog as data
Pricing, context length and capabilities for the whole catalog, so you can route on facts rather than a hardcoded list.
Scale
300+ models from 50+ providers, including every major lab.
Meta · Mistral · DeepSeek · Qwen · xAI
and 50+ more
What we do not have yet
Rather than let you find out during an evaluation.
SOC 2 / ISO 27001
Not certified. We can walk you through our controls and our subprocessors today, and we start the audit when a customer needs it.
On request
Contractual SLA
No uptime guarantee in writing. Per-provider uptime is published live on every model page.
Not yet
Written docs for the agent API
The run, schedule and sandbox endpoints are live and we build on them ourselves. The reference is not written, so today it is a conversation.
On request
On-prem or VPC deployment
Everything runs on our infrastructure.
Not yet
Start with a free key.
Sign in to Mume AI, create an API key from the dashboard, and point your client at it. Volume pricing is a conversation, not a form.
