How to Use the iFLYTEK Open Platform / 讯飞开放平台 MCP in CrewAI

Deploy a team of specialized CrewAI agents to transcribe, translate, and analyze audio using the iFLYTEK Open Platform MCP Server.

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Connect iFLYTEK Open Platform / 讯飞开放平台 MCP to CrewAI

Create your Vinkius account to connect iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台 with CrewAI

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Coordinate translation tasks with CrewAI

`translate` converts content between languages while a specialized editor agent reviews the output for stylistic consistency. In a CrewAI setup, one agent generates the translation, while a second agent suggests localized phrasing. This division of labor improves localization quality. Instead of relying on a single raw translation pass, your autonomous crew collaborates to refine the output before publishing.

Transcribe and summarize audio via MCP Server

`speech_to_text` transcribes long audio recordings, passing the raw transcript to a summarizer agent. This agent uses `summary_generation` to extract key action items and decisions from the meeting notes. Your team gets clean meeting summaries without manual effort. The sequential execution model in CrewAI ensures that the transcription completes fully before the summarization agent begins its analysis.

Extract insights from unstructured text

`keyword_extraction` identifies the core themes of a document, which a researcher agent then cross-references with named entities from `entity_recognition`. Your CrewAI agents use this combined data to build structured market intelligence reports. You automate complex market research tasks. By dividing the extraction and analysis across specialized agents, the system avoids context-window limits and produces highly focused reports.

Setup guide

Set up iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台 tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="iFLYTEK Open Platform / 讯飞开放平台 Analyst",
    goal="Access and analyze iFLYTEK Open Platform / 讯飞开放平台 data via MCP.",
    backstory="Expert analyst with direct iFLYTEK Open Platform / 讯飞开放平台 access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent iFLYTEK Open Platform / 讯飞开放平台 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="iFLYTEK Open Platform / 讯飞开放平台 Analyst",
        goal="Access and analyze iFLYTEK Open Platform / 讯飞开放平台 data via MCP.",
        backstory="Expert analyst with direct iFLYTEK Open Platform / 讯飞开放平台 access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台. 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 iFLYTEK Open Platform / 讯飞开放平台 MCP in CrewAI

You pass the MCP Server URL to the agent's tool configuration array. You can give the transcriber agent access to `speech_to_text` while restricting the analyst agent to `summary_generation`.

Yes, a writer agent can draft a script, and a voice agent can then use `text_to_speech` to generate the final audio file. They share state through CrewAI's memory features.

You configure your transcribing agent to chunk the audio before passing it to `speech_to_text`. This prevents timeout issues and allows parallel processing across your crew.

No, Vinkius hosts and manages the server infrastructure. Your CrewAI scripts connect directly to the managed endpoint, reducing your local deployment footprint.

Your text data and audio payloads pass through encrypted channels to the iFLYTEK endpoints. The Vinkius sandbox operates ephemerally, meaning your proprietary transcripts and documents are never cached or stored.

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