Convex MCP Server for CrewAIGive CrewAI instant access to 4 tools to Run Action, Run Function, Run Mutation, and more
Connect your CrewAI agents to Convex through Vinkius, pass the Edge URL in the `mcps` parameter and every Convex tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The Convex MCP Server for CrewAI is a standout in the Loved By Devs category — giving your AI agent 4 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
from crewai import Agent, Task, Crew
agent = Agent(
role="Convex Specialist",
goal="Help users interact with Convex effectively",
backstory=(
"You are an expert at leveraging Convex tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Convex "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 4 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Convex MCP Server
Connect your Convex deployment to any AI agent and manage your application's data and logic through natural conversation. This server allows you to interact with your real-time database and serverless functions without leaving your AI interface.
When paired with CrewAI, Convex becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Convex tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
What you can do
- Data Fetching — Execute read-only queries to retrieve documents and state from your Convex tables.
- Transactional Updates — Run mutations to modify data with full ACID guarantees directly from the agent.
- Side Effects & APIs — Trigger Convex actions for external API calls, heavy computation, or non-transactional logic.
- Flexible Execution — Call functions using standard colon notation or URL-style identifiers for maximum compatibility.
The Convex MCP Server exposes 4 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 4 Convex tools available for CrewAI
When CrewAI connects to Convex through Vinkius, your AI agent gets direct access to every tool listed below — spanning real-time-database, serverless-functions, typescript, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Run action on Convex
Call a Convex action function
Run function on Convex
g., "messages/list" instead of "messages:list"). Call a Convex function by its URL identifier
Run mutation on Convex
Call a Convex mutation function
Run query on Convex
Use this for fetching data. Call a Convex query function
Connect Convex to CrewAI via MCP
Follow these steps to wire Convex into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 4 tools from ConvexWhy Use CrewAI with the Convex MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Convex through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Convex + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Convex MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Convex for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Convex, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Convex tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Convex against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Convex in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Convex immediately.
"Run the Convex query 'messages:list' with no arguments."
"Call the mutation 'users:create' with the argument { "name": "Alice" }."
"Execute the function 'tasks/get_all' using run_function."
Troubleshooting Convex MCP Server with CrewAI
Common issues when connecting Convex to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Convex + CrewAI FAQ
Common questions about integrating Convex MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
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