Corina Bodlev
Corina is a Marketing Operations Specialist at BLEND, driving the processes and systems that keep marketing campaigns running smoothly and efficiently.
Machine speed to order. Human quality to deliver.
Here’s a workflow you’ve probably lived through: you’re deep in a conversation with Claude or Cursor, building the next version of your product, and you hit a wall that has nothing to do with code. Something needs to be translated. So you stop. You copy the string out of your editor, open a browser tab, log into a translation portal you use twice a quarter, paste it in, wait, check back later, and eventually copy the result back into your codebase.
None of that friction was ever about translation quality. It was about distance: the gap between where the work happens and where the translation platform lives.
We just closed that gap.
BLEND now publishes an MCP server. If you haven’t run into Model Context Protocol yet, here’s the short version: it’s the open standard AI assistants use to reach outside their own context and actually do things, the same way they already read a file or run a query. We built a server that speaks it.
Connect once, from Claude Desktop, Claude on the web, Claude Code, or any other MCP client, and your agent gains 8 tools. From there, it can quote a job, place the order, track a linguist’s progress, and hand you back the finished files, without you ever leaving the conversation.

One thing worth being precise about, because it’s easy to blur: MCP is an ordering layer, not a translation-generation layer. Your agent isn’t the one translating. It’s doing the legwork around the translation, discovery, pricing, ordering, status checks, retrieval, while a real, vetted BLEND linguist does the actual work. That’s a different claim than “your agent calls our engine,” and it’s the one we’re making.
Nothing about the translation itself gets faster. Human work still takes hours to days, and we’re not pretending otherwise.
What disappears is everything around the translation: exporting content out of your tool, opening a portal, uploading files, checking back repeatedly, then moving finished files back to where the work actually lives. With MCP, you ask in the conversation you’re already having. Your agent prices it and shows you the quote before it spends a cent. You approve. It tracks progress on its own schedule. The translated files land back in that same conversation.
No new platform to log into. No API keys to generate, copy, and eventually forget to rotate. You authenticate once with your existing BLEND account over standard OAuth, and the agent never sees your password.
Handing an agent the ability to spend money on your behalf is exactly the kind of thing that should make you pause, so here’s what we built in rather than bolted on:
And the ordering isn’t limited to the “human translation” framing in the headline. The same connection covers 7 project types, from straight machine translation through MTPE and full professional translation and editing, so whatever quality tier the string actually needs, your agent can order the right one.
In one real session, an agent was asked to quote an English-to-Ukrainian marketing job. It found there was no configured rate for that specific language pair and expertise combination, the kind of gap that would normally mean a support ticket or a shrug. It didn’t guess.
It flagged the gap. Proposed ordering under general expertise instead, with the marketing tone carried in the linguist notes. Priced it at $4.55. Then said plainly that approving would place a real, charged order.
That’s the trust design above, not as a bullet point, but as something that actually happened. The agent did the legwork. A human still decided when the money moved.
We could have shipped “a translation API your agent can call” and called it a day. We didn’t, because the honest bottleneck was never the engine. It’s everything wrapped around getting real translation work in front of a real linguist and back again.
We’ve spent 18+ years being the company scaling software companies call when localization needs to stop being a manual step blocking deployment. The AI-first startups showed up with the technology but not the track record. The legacy players had the track record but never rebuilt for how software actually gets shipped today. MCP is us betting that the next place localization needs to live isn’t a dashboard at all. It’s wherever the work is already happening, which increasingly means inside a conversation with an AI agent.
Connect at www.getblend.com/mcp/. Your agent does the legwork. You still decide when money moves.
What our customers are saying