How to Use the Asian Development Bank MCP in CrewAI

Q: How do I restrict Asian Development Bank access to specific CrewAI roles?

Use the toolfilter parameter within the MCP HTTP configuration. This limits specific agents to only fetching GDP or inflation numbers based on their assigned duties.

Deploy autonomous economic research crews using CrewAI and the Asian Development Bank database.

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Connect Asian Development Bank MCP to CrewAI

Create your Vinkius account to connect Asian Development Bank 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 Asian Development Bank with CrewAI

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Multi-Agent Economic Research

Equipping your researcher agent with `query_adb_indicators` allows it to pull raw macroeconomic data from 49 APAC countries. The agent queries specific dataflow IDs, gathers the results, and passes the dataset to a specialized analyst agent in shared memory. Passing the Vinkius URL directly into the mcps array gives your entire crew immediate access to these endpoints. You build hierarchical teams where one AI focuses entirely on data extraction while another writes the final market report.

Autonomous Inflation Monitoring

The `get_inflation_asia` tool lets a dedicated monitor agent track consumer price index changes across the region. When the agent detects a spike in Thailand's inflation, it alerts a moderator agent to take action. This completely removes humans from the initial data gathering phase. Your specialized crew continuously evaluates the economic metrics and only escalates when predefined conditions are met.

Asian Development Bank MCP Server Integration

Calling `get_gdp_asia` feeds real-time gross domestic product figures directly into your autonomous operations. An analyst agent compares output codes like PRC and JPN to generate cross-border trade insights. For advanced setups, you filter exactly which tools each agent sees using the MCP server configuration. A researcher gets full access to the database, while a writer agent only receives the processed summaries.

Setup guide

Set up Asian Development Bank 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 Asian Development Bank tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Asian Development Bank 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="Asian Development Bank Analyst",
        goal="Access and analyze Asian Development Bank data via MCP.",
        backstory="Expert analyst with direct Asian Development Bank access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Asian Development Bank 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Asian Development Bank. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Asian Development Bank MCP in CrewAI

Add the Vinkius URL to the mcps parameter when defining your agent. The framework automatically discovers and registers the available data tools.

Yes. Your entire crew can hit the endpoints during their respective execution phases. Shared memory ensures they don't duplicate identical data requests.

Use the tool_filter parameter within the MCP HTTP configuration. This limits specific agents to only fetching GDP or inflation numbers based on their assigned duties.

The setup supports stdio, SSE, and Streamable HTTP. Vinkius provides an HTTP endpoint that plugs right into your crew's configuration.

Every request for APAC trade balances or population statistics routes through a zero-trust architecture. The managed connection authenticates via a single token and destroys the execution context the second your agents receive their data.

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