How to Use the Delivery Integrity Prover MCP in CrewAI

Stop your CrewAI agents from passing incomplete work down the line by forcing strict task validation.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Delivery Integrity Prover MCP to CrewAI

Create your Vinkius account to connect Delivery Integrity Prover 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 Delivery Integrity Prover with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Inter-agent quality control

Autonomous teams fall apart when one agent hands off garbage to the next. You assign this MCP Server to a QA agent to enforce strict standards. It runs `verify_delivery` to check the working agent's output against the original prompt requirements. The reviewing agent demands empirical validation logs and exact modified file paths. If the work falls short, the tool rejects the submission and forces the original agent to fix the highlighted issues.

Autonomous auditing with the Delivery Integrity Prover MCP Server

Your crew needs a reliable way to know when a job is truly done. This integration forces the acting agent to state the task objective clearly and commit to a proposed verdict. It exposes any remaining gaps or limitations before the hierarchical execution moves forward. You get a documented trail of exactly how the agent verified its own work.

Simple crew setup

Getting this MCP Server running takes almost zero effort. You pass the Vinkius endpoint URL directly into your agent's configuration, and the crew immediately understands how to validate its work. Advanced setups can use the HTTP transport layer to filter specific tools. You control exactly which agent gets the power to call `verify_delivery` and declare a task finished.

Setup guide

Set up Delivery Integrity Prover 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 Delivery Integrity Prover tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Delivery Integrity Prover 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 Delivery Integrity Prover. 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 Delivery Integrity Prover 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 Delivery Integrity Prover MCP in CrewAI

Install the framework with the tools extra using pip install crewai "crewai[tools]". Pass the Vinkius URL into the mcps array on your specific QA agent to give it validation capabilities.

Assign this to a dedicated monitor or QA agent in your crew. They will use verify_delivery to audit the work of your execution agents before allowing the sequential process to continue.

The tool forces the model to explicitly document remaining gaps and limitations in plain text. It also requires a strict boolean pivot to indicate a final pass or fail verdict.

Yes, you can use the MCPServerHTTP class from crewai.mcp and apply a tool_filter. This ensures only your designated moderator agent can approve task completions.

Your target files, prompt requirements, and test logs never persist on Vinkius servers. The managed infrastructure uses ephemeral containers that authenticate via a single endpoint token and destroy themselves after the check completes.

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