How to Use the Wiktionary MCP in CrewAI

Q: How does Wiktionary work with CrewAI?

You pass the MCP Server URL containing wiktionary-mcp into your agents. The crew then executes tasks, using tools like getworddefinition to gather information and passing it between specialized roles.

Q: Is the MCP Server compatible with advanced CrewAI setup?

Yes. You can use toolfilter when setting up the server connection if you only want certain tools exposed, keeping your operation clean and focused.

Run autonomous research: Specialized agents analyzing definitions and summaries with CrewAI and Wiktionary.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Wiktionary MCP to CrewAI

Create your Vinkius account to connect Wiktionary 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.

GDPR Free for Subscribers

Setup Wiktionary with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous Linguistic Research

You don't run one agent; you set up a crew. One specialized agent can be dedicated to calling `get_word_definition` repeatedly, while another focuses solely on structuring the output using `get_word_summary`. The collaboration between roles handles the full research cycle without needing constant human prompts.

Role-Based Specialization

CrewAI allows you to assign specialized tools. You can give Agent A access only to definition tools, and Agent B access only to summary tools. This containment keeps the research focused. The shared memory ensures that definitions found by Agent A are available for analysis by Agent B.

Monitor Complex Tool Execution

The system monitor agent watches the entire session, tracking every call to the MCP Server. If multiple agents are running searches and summaries simultaneously, the moderator keeps track of who needs to act next. This is ideal for large-scale, unsupervised content generation.

Setup guide

Set up Wiktionary 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 Wiktionary tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Wiktionary 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 Wiktionary. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Wiktionary now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Wiktionary MCP in CrewAI

You pass the MCP Server URL containing `wiktionary-mcp` into your agents. The crew then executes tasks, using tools like `get_word_definition` to gather information and passing it between specialized roles.

Yes, the framework supports parallel task execution. You can assign several agents to run different definition or summary checks at once, speeding up your research time.

The server handles linguistic content: definitions, summaries, and examples. The crew uses this text data to build its final report or analysis.

Yes. You can use `tool_filter` when setting up the server connection if you only want certain tools exposed, keeping your operation clean and focused.

The MCP Server only touches linguistic texts: definitions and summaries. Since it's content-based knowledge, the system doesn't process or require any user personal identifiers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript