How to Use the N-Gram Frequency Engine MCP in CrewAI

Q: How do I add the N-Gram Frequency Engine to my CrewAI agents?

Pass the server URL in the mcps list when defining your agent. This automatically exposes extractngramfrequencies to your crew members.

Deploy autonomous research crews with the N-Gram Frequency Engine. Get exact counts for your CrewAI agents.

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Connect N-Gram Frequency Engine MCP to CrewAI

Create your Vinkius account to connect N-Gram Frequency Engine 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 N-Gram Frequency Engine with CrewAI

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Claude

Perplexity

Specialized linguistic analysis for CrewAI

Assign a dedicated agent in your crew to use `extract_ngram_frequencies` for gathering insights. While your researcher agent finds the text, your analyst agent uses this server to get precise frequency distributions. This role-based specialization keeps your agents focused. The analyst agent doesn't need to know how to parse text; it just asks the tool for the numbers.

Deterministic data for autonomous operations

Your agents can make better decisions when they have exact counts. The N-Gram Frequency Engine provides the hard data your crew needs to monitor trends or detect anomalies in large datasets. It removes the guesswork from your agent's reasoning. Instead of guessing if a phrase is important, the crew knows exactly how many times it appeared.

Collaborative memory with accurate counts

Share the output of the N-Gram Frequency Engine across your crew's memory. Once one agent extracts the frequencies, the rest of the crew can use that data to coordinate their next moves. This is essential for hierarchical workflows. The moderator agent can review the frequency map and decide if the crew needs to escalate the task or finish the job.

Setup guide

Set up N-Gram Frequency Engine 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 N-Gram Frequency Engine tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent N-Gram Frequency Engine transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="N-Gram Frequency Engine Analyst",
        goal="Access and analyze N-Gram Frequency Engine data via MCP.",
        backstory="Expert analyst with direct N-Gram Frequency Engine access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent N-Gram Frequency Engine 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 N-Gram Frequency Engine MCP in CrewAI

Pass the server URL in the `mcps` list when defining your agent. This automatically exposes `extract_ngram_frequencies` to your crew members.

They can. Because it is an MCP server, any agent in your crew with the tool enabled can access the frequency data during the mission.

It works perfectly. The output from one step is easily passed to the next agent, allowing for a smooth flow from text discovery to frequency analysis.

The server is built for deterministic counting. It will give you the same accurate results every time, which is key for autonomous agents that cannot afford to hallucinate numbers.

All processing happens in an isolated sandbox. Your raw text is used only to calculate the n-gram frequencies and is never written to disk or stored after the process ends.

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