FRED Tags & Sources — Data Discovery MCP Server for LangChain 3 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect FRED Tags & Sources — Data Discovery through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"fred-tags-sources-data-discovery": {
"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 FRED Tags & Sources — Data Discovery, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 FRED Tags & Sources — Data Discovery MCP Server
The discovery layer for FRED. Tags & Sources helps your AI agent find exactly the right series by filtering through FRED's comprehensive tagging system.
LangChain's ecosystem of 500+ components combines seamlessly with FRED Tags & Sources — Data Discovery through native MCP adapters. Connect 3 tools via the 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
- Search Tags — Browse geographic (usa, europe), topic (gdp, inflation), source (bls, bea), and frequency (monthly, quarterly) tags
- Tag Combinations — Find series matching ALL specified tags (e.g., usa + gdp + quarterly) while excluding others
- Data Sources — List all 107 organizations contributing data: BLS, BEA, Federal Reserve Board, Census Bureau, Treasury, IMF, and more
The FRED Tags & Sources — Data Discovery MCP Server exposes 3 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 FRED Tags & Sources — Data Discovery to LangChain via MCP
Follow these steps to integrate the FRED Tags & Sources — Data Discovery 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 3 tools from FRED Tags & Sources — Data Discovery via MCP
Why Use LangChain with the FRED Tags & Sources — Data Discovery MCP Server
LangChain provides unique advantages when paired with FRED Tags & Sources — Data Discovery through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine FRED Tags & Sources — Data Discovery 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 FRED Tags & Sources — Data Discovery queries for multi-turn workflows
FRED Tags & Sources — Data Discovery + LangChain Use Cases
Practical scenarios where LangChain combined with the FRED Tags & Sources — Data Discovery MCP Server delivers measurable value.
RAG with live data: combine FRED Tags & Sources — Data Discovery tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query FRED Tags & Sources — Data Discovery, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain FRED Tags & Sources — Data Discovery tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every FRED Tags & Sources — Data Discovery tool call, measure latency, and optimize your agent's performance
FRED Tags & Sources — Data Discovery MCP Tools for LangChain (3)
These 3 tools become available when you connect FRED Tags & Sources — Data Discovery to LangChain via MCP:
get_series_by_tags
Powerful for discovering related series. Example: tag_names="usa;gdp" returns all US GDP series. Combine with exclude_tag_names to refine. Get FRED series matching specific tags
list_sources
List all FRED data sources
search_tags
Search by text or get all tags. Tags include geographic (usa, europe), topic (gdp, inflation), source (bls, bea), and frequency (monthly, quarterly) labels. Search or browse FRED tags
Example Prompts for FRED Tags & Sources — Data Discovery in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with FRED Tags & Sources — Data Discovery immediately.
"Find all monthly U.S. GDP-related series"
"List all data sources that contribute to FRED"
"What tags are most popular on FRED?"
Troubleshooting FRED Tags & Sources — Data Discovery MCP Server with LangChain
Common issues when connecting FRED Tags & Sources — Data Discovery to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFRED Tags & Sources — Data Discovery + LangChain FAQ
Common questions about integrating FRED Tags & Sources — Data Discovery MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect FRED Tags & Sources — Data Discovery 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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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 FRED Tags & Sources — Data Discovery to LangChain
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.