Knackly MCP Server for CrewAIGive CrewAI instant access to 8 tools to Create Data Record, Get Record Details, List Catalogs, and more
Connect your CrewAI agents to Knackly through Vinkius, pass the Edge URL in the `mcps` parameter and every Knackly tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this App Connector for CrewAI
The Knackly app connector for CrewAI is a standout in the Productivity category — giving your AI agent 8 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="Knackly Specialist",
goal="Help users interact with Knackly effectively",
backstory=(
"You are an expert at leveraging Knackly 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 Knackly "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 8 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 Knackly MCP Server
Connect your Knackly account to any AI agent and automate document generation through natural conversation.
When paired with CrewAI, Knackly becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Knackly 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
- Template Management — Browse templates and their field configurations
- Document Generation — Create documents from templates with field data
- App Browsing — List all Knackly apps and their configurations
- Generation History — Track document generation history and outputs
The Knackly MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 8 Knackly tools available for CrewAI
When CrewAI connects to Knackly through Vinkius, your AI agent gets direct access to every tool listed below — spanning document-automation, template-assembly, legal-tech, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add a new record
Get details for a specific record
List catalogs in a workspace
List models in a catalog
List records for a model
List automated documents
List configured webhooks
List Knackly workspaces
Connect Knackly to CrewAI via MCP
Follow these steps to wire Knackly into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the 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 8 tools from KnacklyWhy Use CrewAI with the Knackly MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Knackly 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
Knackly + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Knackly MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Knackly 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 Knackly, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Knackly 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 Knackly against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Knackly in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Knackly immediately.
"Show all apps and templates available for document generation."
"Generate an NDA for Acme Corp and show the required fields."
"Show document generation history for this month."
Troubleshooting Knackly MCP Server with CrewAI
Common issues when connecting Knackly to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Knackly + CrewAI FAQ
Common questions about integrating Knackly 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.