Firefish MCP Server for CrewAI 12 tools — connect in under 2 minutes
Connect your CrewAI agents to Firefish through Vinkius, pass the Edge URL in the `mcps` parameter and every Firefish 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="Firefish Specialist",
goal="Help users interact with Firefish effectively",
backstory=(
"You are an expert at leveraging Firefish 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 Firefish "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 12 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 Firefish MCP Server
Connect your Firefish account to any AI agent and automate your recruitment workflows through the Model Context Protocol (MCP). Firefish is a high-performance recruitment CRM that empowers agencies to reach more candidates and close more placements. Now, you can interact with your recruitment data directly through natural conversation.
When paired with CrewAI, Firefish becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Firefish 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
- Candidate Management — List all candidates, fetch detailed profiles, and create new candidate records instantly.
- Job Tracking — Monitor active job vacancies and retrieve complete metadata for any job in your system.
- Company & Contact Insights — Access your database of client companies and contacts to stay informed before meetings or calls.
- Placement Monitoring — Keep track of successful job placements and recruitment progress across your team.
- Advertising Overview — List active job advertisements to see where your recruitment efforts are focused.
- Activity Actions — Retrieve a list of recent recruiter actions to maintain a clear audit trail of engagement.
- Seamless Integration — Securely connect your Firefish environment using your Client ID and Secret for an automated experience.
The Firefish MCP Server exposes 12 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 Firefish to CrewAI via MCP
Follow these steps to integrate the Firefish 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 12 tools from Firefish
Why Use CrewAI with the Firefish MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Firefish 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
Firefish + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Firefish MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Firefish 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 Firefish, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Firefish 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 Firefish against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Firefish MCP Tools for CrewAI (12)
These 12 tools become available when you connect Firefish to CrewAI via MCP:
create_candidate
Create a new candidate
get_candidate
Get candidate details
get_company
Get company details
get_contact
Get contact details
get_job
Get job details
list_actions
List actions
list_adverts
List job adverts
list_candidates
List candidates
list_companies
List companies
list_contacts
List contacts
list_jobs
List jobs
list_placements
List placements
Example Prompts for Firefish in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Firefish immediately.
"List all active job vacancies at Firefish."
"Search for a candidate named 'John Smith'."
"Show me the most recent recruiter actions."
Troubleshooting Firefish MCP Server with CrewAI
Common issues when connecting Firefish 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
Firefish + CrewAI FAQ
Common questions about integrating Firefish 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 Firefish 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.
AI-first code editor with integrated LLM-powered coding assistance.
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 Firefish to CrewAI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.