PhantomBuster connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   .env

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Set up the connector

   Register your PhantomBuster credentials with Scalekit so it can authenticate requests on your behalf. You do this once per environment.

   Dashboard setup steps

   Register your PhantomBuster API key with Scalekit so it can authenticate and proxy automation requests on behalf of your users. PhantomBuster uses API key authentication — there is no redirect URI or OAuth flow.

   1. Get your PhantomBuster API key

      • Sign in to phantombuster.com and go to Settings → API in the left sidebar.

      • Your API key is displayed on this page. Click the copy icon to copy it. If you need a new key, click Regenerate.

      

      Keep your API key secret

      Your PhantomBuster API key grants full access to your organization — including launching agents, reading lead data, and managing billing. Never expose it in client-side code or commit it to source control.

      Plan requirements

      PhantomBuster tools require different subscription tiers. Review the table below before choosing a plan at phantombuster.com/pricing:

      Plan	Included resources	Notes
      Trial	2 hrs execution time/month, 1 agent	Core agent and container tools only
      Starter	20 hrs/month, up to 5 agents	Leads, lists, basic org tools
      Pro	80 hrs/month, up to 15 agents	CRM integration, AI credits, SERP credits
      Team	300 hrs/month, unlimited agents	Custom scripts, branches, full org export
      Business	Custom	SSO, dedicated support, custom limits

      Specific tool requirements:

      • phantombuster_ai_completions — requires AI credits (included in Pro+, or purchasable add-on)
      • phantombuster_org_save_crm_contact — requires a HubSpot CRM integration configured in org settings (Pro+)
      • phantombuster_branch_* — requires custom script access (Team+)
      • phantombuster_org_export_* — requires Pro+ for full date ranges (up to 6 months)

   2. Create a connection in Scalekit

      • In Scalekit dashboard, go to AgentKit > Connections > Create Connection. Find PhantomBuster and click Create.

      • Note the Connection name — you will use this as connection_name in your code (e.g., phantombuster).

      

   3. Add a connected account

      Connected accounts link a specific user identifier in your system to a PhantomBuster API key. Add accounts via the dashboard for testing, or via the Scalekit API in production.

      Via dashboard (for testing)

      • Open the connection you created and click the Connected Accounts tab → Add account.

      • Fill in:

        • Your User’s ID — a unique identifier for this user in your system (e.g., user_123)
        • API Key — the PhantomBuster API key you copied in step 1

      • Click Save.

      

      Via API (for production)

      Node.js

      await scalekit.actions.upsertConnectedAccount({
        connectionName: 'phantombuster',
        identifier: 'user_123',
        credentials: { api_key: 'your-phantombuster-api-key' },
      });

      Python

      scalekit_client.actions.upsert_connected_account(
          connection_name="phantombuster",
          identifier="user_123",
          credentials={"api_key": "your-phantombuster-api-key"}
      )

      Production usage tip

      In production, call upsertConnectedAccount when a user connects their PhantomBuster account — for example, after they paste their API key into a settings page in your app.

   Rate limits

   PhantomBuster enforces per-plan API rate limits. Exceeding them returns 429 Too Many Requests. Monitor your execution time and resource usage at phantombuster.com → Dashboard → Usage.

4. Make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'phantombuster'
   const identifier = 'user_123'
   
   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'phantombuster_org_fetch',
     toolInput: {},
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "phantombuster"
   identifier = "user_123"
   
   # Make your first call
   result = actions.execute_tool(
       tool_input={},
       tool_name="phantombuster_org_fetch",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)

What you can do

Connect this agent connector to let your agent:

• Attach container — Attach to a running PhantomBuster container and stream its console output in real-time
• Launch agent — Launch a PhantomBuster automation agent asynchronously
• Fetch agent, org, lists — Get the output of the most recent container of an agent
• Completions ai — Get an AI text completion from PhantomBuster’s AI service
• Release branch — Release (promote to production) specified scripts on a branch in the current PhantomBuster organization
• Stop agent — Stop a currently running PhantomBuster agent execution

Common workflows

Proxy API call

Node.js

// List all agents via Scalekit proxy — no API key needed here
const result = await actions.request({
  connectionName: 'phantombuster',
  identifier: 'user_123',
  path: '/api/v2/agents',
  method: 'GET',
});
console.log(result.data);

Python

# List all agents via Scalekit proxy — no API key needed here
result = actions.request(
    connection_name='phantombuster',
    identifier='user_123',
    path="/api/v2/agents",
    method="GET"
)
print(result)

No OAuth flow needed

PhantomBuster uses API key auth — unlike OAuth connectors, there is no authorization link or redirect flow. Once you call upsertConnectedAccount (or add an account via the dashboard), your users can make requests immediately.

Launch an agent and retrieve results

The most common PhantomBuster workflow: launch an automation agent, stream its console output while it runs, then read the final result.

examples/phantombuster_launch.py

# Step 1: Find the agent you want to run
agents = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_agents_fetch_all",
    tool_input={}
)
agent_id = agents.result[0]["id"]  # pick the first agent, or filter by name

# Step 2: Launch the agent
launch_result = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_agent_launch",
    tool_input={
        "id": agent_id,
        "output": "result-object",
    }
)
container_id = launch_result.result["containerId"]
print(f"Agent launched. Container ID: {container_id}")

# Step 3: Poll for output until the agent finishes
output_pos = 0
while True:
    output = actions.execute_tool(
        connection_name='phantombuster',
        identifier='user_123',
        tool_name="phantombuster_container_fetch_output",
        tool_input={"id": container_id, "fromOutputPos": output_pos}
    )
    print(output.result.get("output", ""), end="", flush=True)
    output_pos = output.result.get("nextOutputPos", output_pos)
    if output.result.get("status") in ("finished", "error"):
        break
    time.sleep(3)  # poll every 3 seconds

# Step 4: Fetch the structured result
final_result = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_container_fetch_result",
    tool_input={"id": container_id}
)
print("Scraped profiles:", final_result.result)

Save scraped profiles as leads

After a scraping run, bulk-save extracted profiles to a PhantomBuster lead list for downstream CRM enrichment or outreach.

examples/phantombuster_save_leads.py

# First: fetch available lead lists (or create one in the PhantomBuster dashboard)
lists = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_lists_fetch_all",
    tool_input={}
)
list_id = lists.result[0]["id"]  # use the first list, or filter by name

# Bulk-save up to 1,000 profiles in one call — more efficient than looping
actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_leads_save_many",
    tool_input={
        "listId": list_id,
        "leads": [
            {
                "firstName": p.get("firstName"),
                "lastName": p.get("lastName"),
                "email": p.get("email"),
                "linkedinUrl": p.get("linkedinUrl"),
                "company": p.get("company"),
                "jobTitle": p.get("title"),
                "additionalFields": {
                    "source": "phantombuster-scraper",
                    "agentId": agent_id,
                    "containerId": container_id,
                },
            }
            for p in final_result.result
        ],
    }
)
print(f"{len(final_result.result)} leads saved to list {list_id}.")

Check resource usage before running agents

Avoid quota errors by verifying execution time and credit balances before launching a large scraping run.

examples/phantombuster_check_resources.py

resources = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_org_fetch_resources",
    tool_input={}
)

exec_time = resources.result.get("executionTime", {})
ai_credits = resources.result.get("aiCredits", {})

if exec_time.get("remaining", 0) < 30:
    raise RuntimeError(
        f"Insufficient execution time: {exec_time.get('remaining')} min remaining. "
        "Upgrade at phantombuster.com/pricing or wait for your plan to reset."
    )

print(f"Execution time: {exec_time['remaining']} min remaining ({exec_time.get('used')} used)")
print(f"AI credits: {ai_credits.get('remaining', 'N/A')}")

Run AI completions on scraped data

Use PhantomBuster’s AI service to extract structured data from raw agent output — such as parsing job titles into seniority levels or extracting skills from profile summaries.

Requires AI credits

phantombuster_ai_completions consumes AI credits from your plan. Monitor usage at PhantomBuster dashboard → Usage. AI credits are included in Pro+ plans and available as an add-on.

examples/phantombuster_ai_enrichment.py

# Extract structured data from a raw LinkedIn profile headline
completion = actions.execute_tool(
    connection_name='phantombuster',
    identifier='user_123',
    tool_name="phantombuster_ai_completions",
    tool_input={
        "model": "gpt-4o",
        "messages": [
            {
                "role": "system",
                "content": "Extract the seniority level and primary skill from this LinkedIn headline. Return JSON only.",
            },
            {
                "role": "user",
                "content": "Senior Software Engineer at Acme Corp | React, TypeScript, GraphQL",
            },
        ],
        "responseSchema": {
            "type": "object",
            "properties": {
                "seniority": {"type": "string", "enum": ["junior", "mid", "senior", "lead", "exec"]},
                "primarySkill": {"type": "string"},
            },
            "required": ["seniority", "primarySkill"],
        },
    }
)
print("Parsed profile:", completion.result)
# → {'seniority': 'senior', 'primarySkill': 'React'}

LangChain integration

Let an LLM decide which PhantomBuster tool to call based on natural language. This example builds an agent that can manage automation runs and leads in response to user input.

examples/phantombuster_langchain.py

from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_openai_tools_agent
from langchain_core.prompts import (
    ChatPromptTemplate, SystemMessagePromptTemplate,
    HumanMessagePromptTemplate, MessagesPlaceholder, PromptTemplate
)

# Load all PhantomBuster tools in LangChain format. Use page_size=100 so connector tool lists are not truncated.
tools = actions.langchain.get_tools(
    identifier='user_123',
    providers=["PHANTOMBUSTER"],
    page_size=100
)

prompt = ChatPromptTemplate.from_messages([
    SystemMessagePromptTemplate(prompt=PromptTemplate(
        input_variables=[],
        template=(
            "You are a PhantomBuster automation assistant. "
            "Use the available tools to manage agents, check resource usage, "
            "manage leads, and analyse automation run results."
        )
    )),
    MessagesPlaceholder(variable_name="chat_history", optional=True),
    HumanMessagePromptTemplate(prompt=PromptTemplate(
        input_variables=["input"], template="{input}"
    )),
    MessagesPlaceholder(variable_name="agent_scratchpad")
])

llm = ChatOpenAI(model="gpt-4o")
agent = create_openai_tools_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

result = agent_executor.invoke({
    "input": "List all my agents, show which ones ran in the last 24 hours, and tell me how many leads are in each list"
})
print(result["output"])

Tool list

Use the exact tool names from the Tool list below when you call execute_tool. If you’re not sure which name to use, list the tools available for the current user first.

phantombuster_agent_delete#Permanently delete a PhantomBuster agent and all its associated data. This action is irreversible.1 param▾

Permanently delete a PhantomBuster agent and all its associated data. This action is irreversible.

NameTypeRequiredDescription

agentIdstringrequiredThe unique identifier of the agent to permanently delete.

phantombuster_agent_fetch#Retrieve details of a specific PhantomBuster agent by its ID. Returns agent name, script, schedule, launch type, argument configuration, and current status.1 param▾

Retrieve details of a specific PhantomBuster agent by its ID. Returns agent name, script, schedule, launch type, argument configuration, and current status.

NameTypeRequiredDescription

agentIdstringrequiredThe unique identifier of the agent to retrieve.

phantombuster_agent_fetch_output#Get the output of the most recent container of an agent. Designed for incremental data retrieval — use fromOutputPos to fetch only new output since the last call.5 params▾

Get the output of the most recent container of an agent. Designed for incremental data retrieval — use fromOutputPos to fetch only new output since the last call.

NameTypeRequiredDescription

idstringrequiredID of the agent to fetch output from.

fromOutputPosnumberoptionalStart output from this byte position (for incremental fetching).

prevContainerIdstringoptionalRetrieve output from the container after this previous container ID.

prevRuntimeEventIndexnumberoptionalReturn runtime events starting from this index.

prevStatusstringoptionalPreviously retrieved status from user-side (for delta detection).

phantombuster_agent_launch#Launch a PhantomBuster automation agent asynchronously. Starts the agent execution immediately and returns a container ID to track progress. Use the Get Container Output or Get Container Result tools to retrieve results.4 params▾

Launch a PhantomBuster automation agent asynchronously. Starts the agent execution immediately and returns a container ID to track progress. Use the Get Container Output or Get Container Result tools to retrieve results.

NameTypeRequiredDescription

agentIdstringrequiredThe unique identifier of the agent to launch.

argumentsobjectoptionalJSON object of input arguments to pass to the agent for this execution.

outputstringoptionalOutput mode for the launch response.

saveArgumentsbooleanoptionalWhether to persist the provided arguments as the agent's default arguments for future launches.

phantombuster_agent_launch_soon#Schedule a PhantomBuster agent to launch within a specified number of minutes. Useful for delayed execution without setting up a full recurring schedule.4 params▾

Schedule a PhantomBuster agent to launch within a specified number of minutes. Useful for delayed execution without setting up a full recurring schedule.

NameTypeRequiredDescription

idstringrequiredID of the agent to schedule.

minutesintegerrequiredNumber of minutes from now after which the agent will launch.

argumentobjectoptionalInput arguments to pass to the agent for this execution (object or JSON string).

saveArgumentbooleanoptionalIf true, saves the provided argument as the agent's default for future launches.

phantombuster_agent_save#Create a new PhantomBuster agent or update an existing one. Supports configuring the script, schedule, proxy, notifications, execution limits, and launch arguments. Pass an ID to update; omit to create.13 params▾

Create a new PhantomBuster agent or update an existing one. Supports configuring the script, schedule, proxy, notifications, execution limits, and launch arguments. Pass an ID to update; omit to create.

NameTypeRequiredDescription

argumentobjectoptionalDefault launch argument for the agent (object or JSON string).

branchstringoptionalScript branch to use (e.g., main, staging).

executionTimeLimitnumberoptionalMaximum execution time in seconds before the agent is killed.

idstringoptionalID of the agent to update. Omit to create a new agent.

launchTypestringoptionalHow the agent is launched.

maxParallelismnumberoptionalMaximum number of concurrent executions allowed for this agent.

maxRetryNumbernumberoptionalMaximum number of retries before aborting on failure.

namestringoptionalDisplay name for the agent.

proxyAddressstringoptionalHTTP proxy address or proxy pool name.

proxyPasswordstringoptionalProxy authentication password.

proxyTypestringoptionalProxy configuration type.

proxyUsernamestringoptionalProxy authentication username.

scriptstringoptionalScript slug or name to assign to this agent.

phantombuster_agent_stop#Stop a currently running PhantomBuster agent execution. Gracefully halts the agent and saves any partial results collected up to that point.1 param▾

Stop a currently running PhantomBuster agent execution. Gracefully halts the agent and saves any partial results collected up to that point.

NameTypeRequiredDescription

agentIdstringrequiredThe unique identifier of the agent to stop.

phantombuster_agents_fetch_all#Retrieve all automation agents in the PhantomBuster organization. Returns agent IDs, names, associated scripts, schedules, and current status.0 params▾

Retrieve all automation agents in the PhantomBuster organization. Returns agent IDs, names, associated scripts, schedules, and current status.

phantombuster_agents_fetch_deleted#Retrieve all deleted agents in the PhantomBuster organization. Returns agent IDs, names, creation timestamps, deletion timestamps, and who deleted each agent.0 params▾

Retrieve all deleted agents in the PhantomBuster organization. Returns agent IDs, names, creation timestamps, deletion timestamps, and who deleted each agent.

phantombuster_agents_unschedule_all#Disable automatic launch for ALL agents in the current PhantomBuster organization. Agents will remain but will only run when launched manually.0 params▾

Disable automatic launch for ALL agents in the current PhantomBuster organization. Agents will remain but will only run when launched manually.

phantombuster_ai_completions#Get an AI text completion from PhantomBuster's AI service. Supports multiple models including GPT-4o and GPT-4.1-mini. Optionally request structured JSON output via a response schema.3 params▾

Get an AI text completion from PhantomBuster's AI service. Supports multiple models including GPT-4o and GPT-4.1-mini. Optionally request structured JSON output via a response schema.

NameTypeRequiredDescription

messagesarrayrequiredArray of conversation messages. Each must have a role (system, assistant, or user) and content string.

modelstringoptionalAI model to use for the completion.

temperaturenumberoptionalSampling temperature (0–2). Lower = more deterministic, higher = more creative.

phantombuster_branch_create#Create a new script branch in the current PhantomBuster organization.1 param▾

Create a new script branch in the current PhantomBuster organization.

NameTypeRequiredDescription

namestringrequiredName for the new branch. Only letters, numbers, underscores, and hyphens allowed. Max 50 characters.

phantombuster_branch_delete#Permanently delete a branch by ID from the current PhantomBuster organization.1 param▾

Permanently delete a branch by ID from the current PhantomBuster organization.

NameTypeRequiredDescription

idstringrequiredID of the branch to delete.

phantombuster_branch_release#Release (promote to production) specified scripts on a branch in the current PhantomBuster organization.2 params▾

Release (promote to production) specified scripts on a branch in the current PhantomBuster organization.

NameTypeRequiredDescription

namestringrequiredName of the branch to release.

scriptIdsarrayrequiredArray of script IDs to release on this branch.

phantombuster_branches_fetch_all#Retrieve all branches associated with the current PhantomBuster organization.0 params▾

Retrieve all branches associated with the current PhantomBuster organization.

phantombuster_container_attach#Attach to a running PhantomBuster container and stream its console output in real-time. Returns a live stream of log lines as the agent executes.1 param▾

Attach to a running PhantomBuster container and stream its console output in real-time. Returns a live stream of log lines as the agent executes.

NameTypeRequiredDescription

idstringrequiredID of the running container to attach to.

phantombuster_container_fetch#Retrieve a single PhantomBuster container by its ID. Returns status, timestamps, launch type, exit code, and optionally the full output, result object, and runtime events.5 params▾

Retrieve a single PhantomBuster container by its ID. Returns status, timestamps, launch type, exit code, and optionally the full output, result object, and runtime events.

NameTypeRequiredDescription

idstringrequiredID of the container to fetch.

withNewerAndOlderContainerIdbooleanoptionalSet to true to include the IDs of the next and previous containers for this agent.

withOutputbooleanoptionalSet to true to include the container's console output.

withResultObjectbooleanoptionalSet to true to include the container's result object.

withRuntimeEventsbooleanoptionalSet to true to include runtime events (progress, notifications, etc.).

phantombuster_container_fetch_output#Retrieve the console output and execution logs of a specific PhantomBuster container (agent run). Useful for monitoring execution progress, debugging errors, and viewing step-by-step agent activity.1 param▾

Retrieve the console output and execution logs of a specific PhantomBuster container (agent run). Useful for monitoring execution progress, debugging errors, and viewing step-by-step agent activity.

NameTypeRequiredDescription

containerIdstringrequiredThe unique identifier of the container whose output to retrieve.

phantombuster_container_fetch_result#Retrieve the final result object of a completed PhantomBuster container (agent run). Returns the structured data extracted or produced by the agent, such as scraped profiles, leads, or exported records.1 param▾

Retrieve the final result object of a completed PhantomBuster container (agent run). Returns the structured data extracted or produced by the agent, such as scraped profiles, leads, or exported records.

NameTypeRequiredDescription

containerIdstringrequiredThe unique identifier of the container whose result to retrieve.

phantombuster_containers_fetch_all#Retrieve all execution containers (past runs) for a specific PhantomBuster agent. Returns container IDs, status, launch type, exit codes, timestamps, and runtime events for each execution.1 param▾

Retrieve all execution containers (past runs) for a specific PhantomBuster agent. Returns container IDs, status, launch type, exit codes, timestamps, and runtime events for each execution.

NameTypeRequiredDescription

agentIdstringrequiredThe unique identifier of the agent whose containers to retrieve.

phantombuster_leads_delete_many#Permanently delete multiple leads from PhantomBuster organization storage by their IDs.1 param▾

Permanently delete multiple leads from PhantomBuster organization storage by their IDs.

NameTypeRequiredDescription

idsarrayrequiredArray of lead IDs to delete.

phantombuster_leads_fetch_by_list#Fetch paginated leads belonging to a specific lead list in PhantomBuster organization storage.5 params▾

Fetch paginated leads belonging to a specific lead list in PhantomBuster organization storage.

NameTypeRequiredDescription

listIdstringrequiredID of the lead list to fetch leads from.

includeTotalCountbooleanoptionalInclude the total count of leads in the response.

paginationOffsetintegeroptionalOffset for pagination.

paginationOrderstringoptionalSort order for pagination.

paginationSizeintegeroptionalNumber of leads per page.

phantombuster_leads_save#Save a single lead to PhantomBuster organization storage.1 param▾

Save a single lead to PhantomBuster organization storage.

NameTypeRequiredDescription

leadobjectrequiredLead data object to save.

phantombuster_leads_save_many#Save multiple leads at once to PhantomBuster organization storage.1 param▾

Save multiple leads at once to PhantomBuster organization storage.

NameTypeRequiredDescription

leadsarrayrequiredArray of lead objects to save.

phantombuster_list_delete#Permanently delete a lead list from PhantomBuster organization storage by its ID.1 param▾

Permanently delete a lead list from PhantomBuster organization storage by its ID.

NameTypeRequiredDescription

idstringrequiredID of the lead list to delete.

phantombuster_list_fetch#Retrieve a specific lead list from PhantomBuster organization storage by its ID.1 param▾

Retrieve a specific lead list from PhantomBuster organization storage by its ID.

NameTypeRequiredDescription

idstringrequiredID of the lead list to fetch.

phantombuster_lists_fetch_all#Retrieve all lead lists in the PhantomBuster organization's storage.0 params▾

Retrieve all lead lists in the PhantomBuster organization's storage.

phantombuster_location_ip#Retrieve the country associated with an IPv4 or IPv6 address using PhantomBuster's geolocation service.1 param▾

Retrieve the country associated with an IPv4 or IPv6 address using PhantomBuster's geolocation service.

NameTypeRequiredDescription

ipstringrequiredIPv4 or IPv6 address to look up.

phantombuster_org_export_agent_usage#Export a CSV file containing agent usage metrics for the current PhantomBuster organization over a specified number of days (max 6 months).1 param▾

Export a CSV file containing agent usage metrics for the current PhantomBuster organization over a specified number of days (max 6 months).

NameTypeRequiredDescription

daysstringrequiredNumber of days of usage data to export. Maximum is ~180 days (6 months).

phantombuster_org_export_container_usage#Export a CSV file containing container usage metrics for the current PhantomBuster organization. Optionally filter to a specific agent.2 params▾

Export a CSV file containing container usage metrics for the current PhantomBuster organization. Optionally filter to a specific agent.

NameTypeRequiredDescription

daysstringrequiredNumber of days of usage data to export. Maximum is ~180 days (6 months).

agentIdstringoptionalFilter the export to a specific agent ID.

phantombuster_org_fetch#Retrieve details of the current PhantomBuster organization including plan, billing, timezone, proxy config, and CRM integrations.4 params▾

Retrieve details of the current PhantomBuster organization including plan, billing, timezone, proxy config, and CRM integrations.

NameTypeRequiredDescription

withCrmIntegrationsbooleanoptionalInclude the organization's CRM integrations.

withCustomPromptsbooleanoptionalInclude the organization's custom prompts.

withGlobalObjectbooleanoptionalInclude the organization's global object in the response.

withProxiesbooleanoptionalInclude the organization's proxy pool configuration.

phantombuster_org_fetch_agent_groups#Retrieve the agent groups and their ordering for the current PhantomBuster organization.0 params▾

Retrieve the agent groups and their ordering for the current PhantomBuster organization.

phantombuster_org_fetch_resources#Retrieve the current PhantomBuster organization's resource usage and limits. Returns daily and monthly usage for execution time, mail, captcha, AI credits, SERP credits, storage, and agent count.0 params▾

Retrieve the current PhantomBuster organization's resource usage and limits. Returns daily and monthly usage for execution time, mail, captcha, AI credits, SERP credits, storage, and agent count.

phantombuster_org_fetch_running_containers#List all currently executing containers across the PhantomBuster organization. Returns container IDs, associated agent IDs/names, creation timestamps, launch types, and script slugs.0 params▾

List all currently executing containers across the PhantomBuster organization. Returns container IDs, associated agent IDs/names, creation timestamps, launch types, and script slugs.

phantombuster_org_save_agent_groups#Update the agent groups and their ordering for the current PhantomBuster organization. The order of groups and agents within groups is preserved as provided.1 param▾

Update the agent groups and their ordering for the current PhantomBuster organization. The order of groups and agents within groups is preserved as provided.

NameTypeRequiredDescription

agentGroupsarrayrequiredArray of agent groups. Each item is either an agent ID string or an object with id, name, and agents array.

phantombuster_org_save_crm_contact#Save a new contact to the organization's connected CRM (HubSpot). Requires a CRM integration to be configured in the PhantomBuster organization settings.8 params▾

Save a new contact to the organization's connected CRM (HubSpot). Requires a CRM integration to be configured in the PhantomBuster organization settings.

NameTypeRequiredDescription

crmNamestringrequiredThe CRM to save the contact to.

firstnamestringrequiredContact's first name.

lastnamestringrequiredContact's last name.

pb_linkedin_profile_urlstringrequiredLinkedIn profile URL of the contact.

companystringoptionalCompany the contact works at.

emailstringoptionalContact's email address.

jobtitlestringoptionalContact's job title.

phonestringoptionalContact's phone number.

phantombuster_script_fetch#Retrieve a specific PhantomBuster script by ID including its manifest, argument schema, output types, and optionally the full source code.3 params▾

Retrieve a specific PhantomBuster script by ID including its manifest, argument schema, output types, and optionally the full source code.

NameTypeRequiredDescription

idstringrequiredID of the script to fetch.

branchstringoptionalBranch of the script to fetch.

withCodebooleanoptionalSet to true to include the script's source code in the response.

phantombuster_scripts_fetch_all#Retrieve all scripts associated with the current PhantomBuster user. Returns script IDs, names, slugs, descriptions, branches, and manifest details.3 params▾

Retrieve all scripts associated with the current PhantomBuster user. Returns script IDs, names, slugs, descriptions, branches, and manifest details.

NameTypeRequiredDescription

branchstringoptionalFilter scripts by branch name.

excludestringoptionalExclude modules or non-modules from results.

orgstringoptionalFilter scripts by organization.