About Voix contact
Reach a human at Voix: submit the studio contact form and get a reply by email
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://lbm.co/mcpclaude mcp add --transport http co-lbm-contact https://lbm.co/mcp{"mcpServers":{"co-lbm-contact":{"type":"http","url":"https://lbm.co/mcp"}}}Open in Cursor{"servers":{"co-lbm-contact":{"type":"http","url":"https://lbm.co/mcp"}}}Open in VS Code{"mcpServers":{"co-lbm-contact":{"type":"http","url":"https://lbm.co/mcp"}}}{"mcpServers":{"co-lbm-contact":{"serverUrl":"https://lbm.co/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
2| Parameter | Type | Required | Description |
|---|---|---|---|
| name | string | Yes | Full name of the person making the enquiry. |
| string | Yes | Email address to reply to. Must be one the person gave you — the answer goes here, so a guessed address means they never hear back. | |
| phone | string | No | Phone number, if they would rather be called than emailed. |
| scope | enum | No | The kind of work the enquiry is about. Pick the closest match only if it is clear from what they told you.Websites | Web applications | Mobile applications | Voix integration | Not sure yet |
| budget | enum | No | Indicative budget, only if the person has actually shared one. Never estimate this on their behalf.Under $25k | $25-50k | $50-100k | $100-250k | $250k+ | Not sure yet |
| company | string | No | Company or organisation they are enquiring on behalf of, if they mentioned one. |
| message | string | Yes | What the enquiry is about, in the person's own words: what they are building, what they need from us, and any deadline they are working to. |
Details
The maintainer has not added details yet. Check the README in the repository.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.