The REST Bridge is a simplified HTTP interface for calling MCP tools. Instead of JSON-RPC framing, you send the tool name and params directly and get the result back.
Endpoint POST https://mcp.supersonic.cv/api/developers/mcp/call/
{ "tool" : "records.list" , "params" : { "object_type_slug" : "companies" , "page" : 1 , "page_size" : 25 } }
Field Type Description toolstringThe MCP tool name (e.g., records.create) paramsobjectTool parameters — same as MCP arguments
{ "success" : true , "data" : { ... } }
On error:
{ "success" : false , "error" : { "code" : "NOT_FOUND" , "message" : "Record not found" } }
Authentication Same as the MCP endpoint — pass your API key in the Authorization header:
Authorization: Bearer supersonic_live_abc123...
Code Examples Python (httpx)
TypeScript (fetch)
curl
import httpx client = httpx.Client( base_url = "https://mcp.supersonic.cv" , headers = { "Authorization" : "Bearer supersonic_live_abc123..." } ) # Create a company result = client.post( "/api/developers/mcp/call/" , json = { "tool" : "records.create" , "params" : { "object_type_slug" : "companies" , "data" : { "Name" : "Acme Corp" , "Domain" : "acme.com" } } }) company = result.json()[ "data" ] print ( f "Created: { company[ 'id' ] } " ) # List deals in a pipeline result = client.post( "/api/developers/mcp/call/" , json = { "tool" : "lists.entries" , "params" : { "list_id" : "lst_abc123" } }) for entry in result.json()[ "data" ]: print ( f " { entry[ 'data' ][ 'Name' ] } : { entry[ 'data' ][ 'Stage' ] } " )
The REST Bridge is ideal for simple integrations and scripts. For AI agents and LLM tool-use, connect directly to the MCP endpoint at https://mcp.supersonic.cv/ using the MCP protocol.
REST Bridge vs MCP REST Bridge MCP (JSON-RPC) URL /api/developers/mcp/call/https://mcp.supersonic.cv/Format { tool, params }JSON-RPC 2.0 with tools/call method Tool discovery Not supported — refer to docs tools/list methodBest for Scripts, webhooks, simple integrations AI agents, LLM tool-use, MCP clients Auth Bearer token Bearer token