How to Use the BLS Public Data API MCP in CrewAI

Coordinate autonomous research crews with CrewAI using the BLS Public Data API for labor market intelligence.

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Connect BLS Public Data API MCP to CrewAI

Create your Vinkius account to connect BLS Public Data API to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup BLS Public Data API with CrewAI

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Monitor BLS Public Data API in CrewAI crews

Assign a monitor agent to call `check_api_status` at the start of your mission. It ensures the crew doesn't waste cycles if the data feed is offline. This creates a smart start to your automated operations. Your other agents only activate once the monitor confirms the environment is ready.

Collaborative economic data analysis

Give your researchers access to `get_bls_timeseries_data` to feed historical stats into the crew's shared memory. One agent pulls the data while another interprets the trends. This specialization allows complex economic reports to form without manual oversight. The agents pass the results back and forth until the task is complete.

Selective tool exposure

Use the tool filter in your MCP configuration to limit which agents see the labor statistics tools. You control the scope of every agent in your crew. This prevents agents from overstepping their roles. It keeps your autonomous operations clean and focused on their specific goal.

Setup guide

Set up BLS Public Data API MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke BLS Public Data API tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="BLS Public Data API Analyst",
    goal="Access and analyze BLS Public Data API data via MCP.",
    backstory="Expert analyst with direct BLS Public Data API access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent BLS Public Data API transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="BLS Public Data API Analyst",
        goal="Access and analyze BLS Public Data API data via MCP.",
        backstory="Expert analyst with direct BLS Public Data API access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent BLS Public Data API transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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Common questions about BLS Public Data API MCP in CrewAI

Add the Vinkius endpoint to the agent's mcp configuration list. The crew will automatically discover and use the tools according to the agent's instructions.

Yes, shared memory allows agents to pass the time series data between themselves. An analyst agent can build on the research gathered by a collection agent.

You only need the endpoint token provided by Vinkius. Once configured, the agents handle the auth headers during the execution of their tasks.

The agents treat the IDs as parameters for the tool call. You can define these in the agent's task description or let the agents generate them dynamically.

Every tool call runs inside an ephemeral, isolated V8 sandbox. Your agents operate in a private space that discards all state once the crew mission finishes.

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