Mattermark MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Mattermark through Vinkius, pass the Edge URL in the `mcps` parameter and every Mattermark tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Mattermark Specialist",
goal="Help users interact with Mattermark effectively",
backstory=(
"You are an expert at leveraging Mattermark 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 Mattermark "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 10 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 Mattermark MCP Server
Connect your Mattermark account to any AI agent and access deep insights into the startup ecosystem through natural conversation.
When paired with CrewAI, Mattermark becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Mattermark 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
- Company Research — Search for startups, fetch detailed metadata, and monitor funding history
- Investor Intelligence — List venture firms and inspect their portfolios and profiles
- Funding Rounds — Query specific investment rounds and their details
- Competitive Analysis — Find similar companies and track employee growth trends
The Mattermark MCP Server exposes 10 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.
How to Connect Mattermark to CrewAI via MCP
Follow these steps to integrate the Mattermark MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 10 tools from Mattermark
Why Use CrewAI with the Mattermark MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Mattermark 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
Mattermark + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Mattermark MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Mattermark 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 Mattermark, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Mattermark 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 Mattermark against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Mattermark MCP Tools for CrewAI (10)
These 10 tools become available when you connect Mattermark to CrewAI via MCP:
get_company_details
Get details for a specific company
get_company_employees
Get employee data for a company
get_company_funding_rounds
Get funding history for a company
get_company_news
Get news for a specific company
get_funding_round_details
Get details for a funding round
get_investor_details
Get details for an investor
list_investors
List venture capital investors
list_similar_companies
Find similar companies
search_companies
Search for companies
search_funding_rounds
Search for funding rounds
Example Prompts for Mattermark in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Mattermark immediately.
"Search for companies in the 'Fintech' sector in New York."
"Get funding history for company ID 123."
"List similar companies to 'Stripe'."
Troubleshooting Mattermark MCP Server with CrewAI
Common issues when connecting Mattermark 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
Mattermark + CrewAI FAQ
Common questions about integrating Mattermark 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.Connect Mattermark with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mattermark to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.