MCP Examples

The examples below show MCP tool inputs. Your client chooses the MCP tool and sends the displayed JSON object.

Discover an operation

Search by outcome:

bctrl_search_api

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{
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  "query": "create agent conversation"
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}

Then inspect the exact operation:

bctrl_get_operation

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{
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  "operationId": "conversations.create"
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}

Start an Agent conversation

Agents attach to an existing Runtime:

bctrl_conversations_create

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{
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  "body": {
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    "runtimeId": "rt_AAAAAAAAAAAAAAAAAAAAAA",
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    "title": "Collect the monthly report"
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  }
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}

Send another message to the ongoing conversation:

bctrl_conversations_messages_create

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{
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  "pathParams": {
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    "conversationId": "conv_AAAAAAAAAAAAAAAAAAAAAA"
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  },
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  "body": {
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    "text": "Open the report and export it as CSV"
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  }
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}

Call a BCTRL Tool synchronously

bctrl_tools_call is the MCP operation tool. stagehand.act is the BCTRL Tool being invoked:

bctrl_tools_call

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{
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  "pathParams": {
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    "toolRef": "stagehand.act"
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  },
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  "headers": {
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    "BCTRL-Runtime-Id": "rt_AAAAAAAAAAAAAAAAAAAAAA"
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  },
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  "body": {
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    "instruction": "Click Continue"
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  }
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}

Create a durable ToolCall

Use durable execution for asynchronous work or capabilities that may require input:

bctrl_tools_calls_create

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{
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  "pathParams": {
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    "toolRef": "captcha.solve"
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  },
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  "headers": {
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    "BCTRL-Runtime-Id": "rt_AAAAAAAAAAAAAAAAAAAAAA"
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  },
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  "body": {
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  }
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}

Read the returned ToolCall:

bctrl_tool_calls_get

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{
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  "pathParams": {
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    "toolCallId": "tc_AAAAAAAAAAAAAAAAAAAAAA"
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  }
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}

If its status is requires_input, inspect prompt and responseSchema, then reply through bctrl_tool_calls_respond.

Inspect one unified Run trace

Agent turns, BCTRL Tool calls, human input, and direct browser automation are correlated under the Run:

bctrl_runs_trace_list

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{
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  "pathParams": {
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    "runId": "run_AAAAAAAAAAAAAAAAAAAAAA"
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  }
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}

Use bctrl_runs_events_list for the raw event record and bctrl_runs_stream for bounded live SSE collection.