How to Use the ElectricSQL (Sync Engine) MCP in CrewAI

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Connect ElectricSQL (Sync Engine) MCP to CrewAI

Create your Vinkius account to connect ElectricSQL (Sync 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 ElectricSQL (Sync Engine) with CrewAI

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Real-time Postgres monitoring for CrewAI

Equip your research agents with `get_shape` to keep them updated on database changes. They always work with the latest state. This removes the need for manual data refreshes. Your crew reacts to new records as they arrive.

Targeted data retrieval in CrewAI

Assign `post_shape` to your analyst agents for deep dives into specific subsets. It lets them filter data before processing. Your crew stays efficient by only analyzing relevant information. It cuts down on unnecessary agent compute time.

Autonomous MCP Server coordination

CrewAI manages the MCP transport across your agent team. You can filter tools so only specific agents access the sync engine. This keeps your operations orderly. You decide which agent gets the power to sync data.

Setup guide

Set up ElectricSQL (Sync 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 ElectricSQL (Sync Engine) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent ElectricSQL (Sync 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 →

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="ElectricSQL (Sync Engine) Analyst",
        goal="Access and analyze ElectricSQL (Sync Engine) data via MCP.",
        backstory="Expert analyst with direct ElectricSQL (Sync Engine) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent ElectricSQL (Sync 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 ElectricSQL (Sync Engine) MCP in CrewAI

Pass the server URL into the agent's MCP list. Once connected, your CrewAI agents can trigger `get_shape` and `post_shape` tools during their tasks.

The agents share the tool outputs through the framework's memory. One agent can sync a shape, and another can analyze that data in the next step.

It is designed for it. The sync engine provides the live data stream that keeps agents informed without human intervention.

You can use the tool filter to limit the scope of the request. This prevents agents from accidentally overwhelming the sync engine.

It uses an isolated sandbox for every connection. Your Postgres credentials never reach the agent, and the server strictly limits access to defined data shapes.

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