plungeai_execute_workflow

Output schema: outcome envelopeCreates an execution: yes

https://mcp.plungeai.com/v1tools/callplungeai_execute_workflow

Authorizations

Authorizationstringheader

Bearer token: Authorization: Bearer ozk_….

X-API-Keystringheader

Alternative header: X-API-Key: ozk_….

Every request needs a key, tools/list included.

Arguments

user_requeststring

The user's original request, verbatim and in their own words, before you translated it into this call. Always include it — the platform uses it for request context, routing and support diagnostics.

Maximum string length: 4000

workflow_yamlstring

one of `workflow_yaml` / `workflow_id`

Ad-hoc CNL workflow YAML. The workflow: wrapper is optional — bare top-level name/tasks is accepted and wrapped automatically.

Maximum string length: 262144

workflow_idstring

one of `workflow_yaml` / `workflow_id`

Maximum string length: 256

inputstring

Maximum string length: 65536

inputsobject

modeenum<string>

Available options: sync, async

Default: sync

formatenum<string>

markdown (default): rendered for an AI reader · json: the same outcome as a JSON document in text plus structuredContent

Available options: markdown, json

Default: markdown

Output

statusenum<string>required

Available options: ok, needs_input, needs_connection, needs_api_key, needs_approval, unavailable, error

summarystringrequired

agent_idstring

operationstring

resultstring

execution_idstring

missingstring[]

warningsstring[]

remediationobject

Show child attributes

messagestringrequired

actionsobject[]required

contractobject

Execute a CNL workflow (saved workflow_id or ad-hoc workflow_yaml). Streams progress. Use mode:"async" for long runs (>3 min) — it returns an execution_id to poll with plungeai_get_workflow_status. In ad-hoc YAML, write long strings as block scalars (prompt: |) — never hard-wrap a value; structured tool-agents take their card's parameters as task fields alongside agent:. Always answers with a structured outcome (never a raw error) — follow the remediation instead of retrying the identical call.

Execute a CNL workflow: a saved one (workflow_id) or ad-hoc YAML (workflow_yaml). Streams progress. Use mode:"async" for long runs (over 3 minutes): it returns an execution id to poll with plungeai_get_workflow_status. In ad-hoc YAML, write long strings as block scalars (prompt: |) and never hard-wrap a value; structured tool-agents take their card's parameters as task fields next to agent:. Always answers with a structured outcome, never a raw error: follow the remediation instead of retrying the identical call.

Returns. ok with the run's output and the execution-id footer. ok with only the execution id for mode:"async". needs_input when neither YAML nor id is given, when the saved id is not on your account (No saved workflow with id `<id>` on this account.), or when the YAML does not parse. unavailable when ad-hoc YAML names an agent that does not exist or is not active, before anything runs. needs_approval / needs_input when the run pauses for you. A failed run is classified into an outcome; an invalid-YAML failure adds a tip on quoting and block scalars.

Runs a model and costs credits (not verified here):

curl -s https://mcp.plungeai.com/v1 \
  -H "Authorization: Bearer $PLUNGE_API_KEY" \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"plungeai_execute_workflow","arguments":{"user_request":"run a one-task pong workflow","workflow_yaml":"name: pong-demo\ntasks:\n  - type: task\n    id: t1\n    agent: llm-agent\n    prompt: \"Reply with only the word: pong\"\n"}}}'

Two parameters recur across the tools: user_request (on every tool: a string of up to 4,000 characters, optional; clients should always send it) and format (markdown by default, or json). Both are described once in Recurring parameters on the MCP overview.

import json import os import requests response = requests.post( "https://mcp.plungeai.com/v1", headers={ "Authorization": f"Bearer {os.environ['PLUNGE_API_KEY']}", "Accept": "application/json, text/event-stream", "Content-Type": "application/json", }, json={ "jsonrpc": "2.0", "id": 1, "method": "tools/call", "params": { "name": "plungeai_execute_workflow", "arguments": {}, }, }, ) for line in response.text.splitlines(): if line.startswith("data: "): print(json.loads(line[6:]))

import { Client } from '@modelcontextprotocol/sdk/client/index.js' import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js' const transport = new StreamableHTTPClientTransport(new URL('https://mcp.plungeai.com/v1'), { requestInit: { headers: { Authorization: `Bearer ${process.env.PLUNGE_API_KEY}` } }, }) const client = new Client({ name: 'my-app', version: '1.0.0' }) await client.connect(transport) const result = await client.callTool({ name: 'plungeai_execute_workflow', arguments: {} }) console.log(result.content)

curl -N -X POST 'https://mcp.plungeai.com/v1' \ -H "Authorization: Bearer $PLUNGE_API_KEY" \ -H 'Accept: application/json, text/event-stream' \ -H 'Content-Type: application/json' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"plungeai_execute_workflow","arguments":{}}}'

{ "jsonrpc": "2.0", "id": 1, "result": { "content": [ { "type": "text", "text": "<string>" } ], "structuredContent": { "status": "ok", "summary": "<string>", "agent_id": "<string>", "operation": "<string>", "result": "<string>", "execution_id": "<string>", "missing": [ "<string>" ], "warnings": [ "<string>" ], "remediation": { "message": "<string>", "actions": [ {} ] }, "contract": {} } } }

plungeai_execute_workflow

Authorizations

Arguments

Output

Planned: TI-33

Planned: TI-34