How to Use the Deterministic Text Summarizer & Extractor MCP in CrewAI

Add deterministic text analysis to your CrewAI multi-agent teams.

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Connect Deterministic Text Summarizer & Extractor MCP to CrewAI

Create your Vinkius account to connect Deterministic Text Summarizer & Extractor 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 Deterministic Text Summarizer & Extractor with CrewAI

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Keyword extraction for CrewAI agents

Give your research agent the `extract_top_keywords` tool to quickly distill long documents. It ignores common noise and gives the agent a list of relevant terms for its next task. This keeps your crew efficient. Instead of reading every page, the agent focuses on the terms that actually appear with the highest frequency.

Bigram phrase detection in CrewAI

Equip your analysis agent with `extract_top_bigrams` to surface common phrases in research data. This helps the team spot specific technical patterns or jargon quickly. It provides a shared foundation for your agents. When every agent sees the same bigram list, they make more consistent decisions during the execution phase.

Extractive summaries for CrewAI pipelines

Use `extractive_summary` to let your monitor agent generate concise reports for the rest of the crew. It extracts the most important sentences based on term density. This ensures your agents stay aligned. By using a deterministic summary, you prevent agents from hallucinating details that weren't in the original document.

Setup guide

Set up Deterministic Text Summarizer & Extractor 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 Deterministic Text Summarizer & Extractor tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Deterministic Text Summarizer & Extractor 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 Deterministic Text Summarizer & Extractor MCP in CrewAI

You pass the server URL into the agent's MCP configuration. The crew will then automatically expose the tools to your specialized agents.

Yes, you can share the tool across your entire crew. Each agent can call it independently to process different documents simultaneously.

It is perfect for research because it provides raw, unbiased data. It helps your research agents extract facts without the risk of generative bias.

It supports standard transport types like SSE and HTTP. You can choose the one that fits your deployment environment, whether it's local or in the cloud.

Your documents stay local to your environment. The tools perform all summarization and extraction on-site, so your sensitive content is never exposed to third-party servers.

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