Bloomberg Law MCP Server for LangChain 13 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Bloomberg Law 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({
"bloomberg-law": {
"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 Bloomberg Law, 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 Bloomberg Law MCP Server
Connect to Bloomberg Law Enterprise Dockets API and access 200 million+ federal and state court records, comprehensive case law database, and Bloomberg Law legal news—all from any AI agent. Search dockets, review filings, track litigation, and stay current on legal developments.
LangChain's ecosystem of 500+ components combines seamlessly with Bloomberg Law through native MCP adapters. Connect 13 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
- Docket Search — Search 200M+ federal and state court dockets by party name, case name, docket number, or keywords
- Federal Dockets — Access District Courts, Circuit Courts of Appeals, Bankruptcy Courts, and Supreme Court dockets
- State Dockets — Search state court dockets across multiple jurisdictions (coverage varies by state)
- Docket Details — Get complete case information including parties, attorneys, judges, and status
- Docket Entries — View all filings, motions, and orders for any docket with timestamps and descriptions
- Filing Documents — Access full text of court filings and documents
- Case Law Search — Search Bloomberg Law's comprehensive case law database for precedents and holdings
- Legal News — Search and browse Bloomberg Law's legal news articles, analysis, and commentary
- Expert Witnesses — Find expert witnesses by specialty, prior testimony, and jurisdiction
- Company Profiles — Search company business intelligence and legal exposure data
- Docket Alerts — View configured alerts monitoring specific cases, parties, or keywords
The Bloomberg Law MCP Server exposes 13 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 Bloomberg Law to LangChain via MCP
Follow these steps to integrate the Bloomberg Law 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 13 tools from Bloomberg Law via MCP
Why Use LangChain with the Bloomberg Law MCP Server
LangChain provides unique advantages when paired with Bloomberg Law through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Bloomberg Law 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 Bloomberg Law queries for multi-turn workflows
Bloomberg Law + LangChain Use Cases
Practical scenarios where LangChain combined with the Bloomberg Law MCP Server delivers measurable value.
RAG with live data: combine Bloomberg Law tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Bloomberg Law, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Bloomberg Law tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Bloomberg Law tool call, measure latency, and optimize your agent's performance
Bloomberg Law MCP Tools for LangChain (13)
These 13 tools become available when you connect Bloomberg Law to LangChain via MCP:
get_case_details
Get detailed information for a specific legal case
get_docket_alerts
Get configured docket alerts for monitoring cases
get_docket_details
Use docket ID from search results. Get detailed information for a specific court docket
get_docket_entries
Each entry includes entry number, filing date, description, and document links. Get all entries/filings for a specific court docket
get_filing_document
Use document ID from docket entries results. Get a specific filing document from a court docket
get_legal_news_by_topic
Get legal news articles by specific topic
search_companies
Search company profiles and business intelligence
search_court_dockets
Returns docket numbers, case names, courts, filing dates, and status. Filter by court, date range, and keywords. Search federal and state court dockets across 200M+ case records
search_expert_witnesses
Find experts by specialty, prior testimony, and jurisdiction. Search for expert witnesses in litigation
search_federal_dockets
Search federal court dockets specifically
search_legal_cases
Returns case summaries, holdings, and outcomes. Filter by jurisdiction and date for precedent analysis. Search for legal cases and case law
search_legal_news
Filter by topic and date range. Search Bloomberg Law legal news articles
search_state_dockets
Coverage varies by state. Search state court dockets
Example Prompts for Bloomberg Law in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Bloomberg Law immediately.
"Search for dockets involving Apple Inc in federal courts."
"Show me the latest legal news on data privacy regulation."
"Get the docket entries for case 1:24-cv-12345 in SDNY."
Troubleshooting Bloomberg Law MCP Server with LangChain
Common issues when connecting Bloomberg Law to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersBloomberg Law + LangChain FAQ
Common questions about integrating Bloomberg Law 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 Bloomberg Law 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 Bloomberg Law to LangChain
Get your token, paste the configuration, and start using 13 tools in under 2 minutes. No API key management needed.