How to Use the Chroma (Vector DB) MCP in CrewAI

Q: How do I link Chroma (Vector DB) to my CrewAI agents?

Pass the server URL in your agent configuration's mcps list. The agents will automatically detect and gain access to the available vector tools.

Q: How do I check the availability of Chroma (Vector DB) in CrewAI?

Include the checkheartbeat tool in a startup task for your lead agent. If the database is down, the agent can alert the team to abort the mission.

Deploy specialized agent crews in CrewAI to research and analyze data stored in Chroma (Vector DB).

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Connect Chroma (Vector DB) MCP to CrewAI

Create your Vinkius account to connect Chroma (Vector DB) 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 Chroma (Vector DB) with CrewAI

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Claude

Perplexity

Collaborative Research with CrewAI

Assign a research agent in your crew to dig into your vector store. It uses `query_embeddings` to pull relevant chunks for the rest of the team to review. This specialization is fast. One agent finds the data, and the other writes the final report based on those findings.

Shared Memory for CrewAI Agents

Let your team of agents reference the same document arrays. Use `get_documents` to ensure every crew member sees the same source material during a task. This keeps your agents aligned. There is no confusion about what document was used to generate an answer.

Vector Database Monitoring in CrewAI

Add a monitor agent to your crew to keep an eye on your database. It uses `peek_documents` to summarize what is inside your collections at any given time. It acts as an automated auditor. Your crew stays informed about the limits and contents of your vector store without you lifting a finger.

Setup guide

Set up Chroma (Vector DB) 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 Chroma (Vector DB) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Chroma (Vector DB) 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 Chroma. 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.

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Common questions about Chroma (Vector DB) MCP in CrewAI

Pass the server URL in your agent configuration's `mcps` list. The agents will automatically detect and gain access to the available vector tools.

Yes, the server handles concurrent requests. Each agent in your crew can run its own independent search against the database without interfering with others.

Yes, you can filter tools so that only specific agents have access. This ensures that only your research-focused crew members can pull data from the vector store.

Include the `check_heartbeat` tool in a startup task for your lead agent. If the database is down, the agent can alert the team to abort the mission.

The connection is isolated within a V8 sandbox. Your sensitive document embeddings are never exposed to other agents or external systems outside your specific crew configuration.

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