How do I ensure the candidate data is up to date?

The Firefish MCP server fetches data directly from your live Firefish environment. Use the 'getCandidate' tool to retrieve the most recent profile information for any specific candidate ID.

Can I filter jobs by their current status?

Yes! The 'listJobs' tool retrieves all active jobs. You can then ask your AI agent to sort or filter these results based on status, title, or hiring company.

What format should I use for creating a new candidate?

Use the 'createCandidate' tool by providing the first name, last name, and email address. The agent will handle the underlying API request to ensure the record is created correctly in Firefish.

Firefish MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Firefish
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Firefish through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "firefish": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Firefish, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Firefish through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Firefish MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Firefish via MCP

Why Use LangChain with the Firefish MCP Server

LangChain provides unique advantages when paired with Firefish through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Firefish MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Firefish queries for multi-turn workflows

Firefish + LangChain Use Cases

Practical scenarios where LangChain combined with the Firefish MCP Server delivers measurable value.

RAG with live data: combine Firefish tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Firefish, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Firefish tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Firefish tool call, measure latency, and optimize your agent's performance

Firefish MCP Tools for LangChain (12)

These 12 tools become available when you connect Firefish to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Firefish to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Firefish + LangChain FAQ

Common questions about integrating Firefish MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.