Salesforce Analytics & SOQL MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Salesforce Analytics & SOQL through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
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({
"salesforce-analytics-soql": {
"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 Salesforce Analytics & SOQL, 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 Salesforce Analytics & SOQL MCP Server
The most powerful Salesforce integration — raw SOQL access to any data in your org.
LangChain's ecosystem of 500+ components combines seamlessly with Salesforce Analytics & SOQL through native MCP adapters. Connect 6 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
- SOQL — Run any query against standard or custom objects
- Reports — List and execute Salesforce reports
- Dashboards — View dashboard components and data
- Counts — Get record counts for any object
The Salesforce Analytics & SOQL MCP Server exposes 6 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 Salesforce Analytics & SOQL to LangChain via MCP
Follow these steps to integrate the Salesforce Analytics & SOQL 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 6 tools from Salesforce Analytics & SOQL via MCP
Why Use LangChain with the Salesforce Analytics & SOQL MCP Server
LangChain provides unique advantages when paired with Salesforce Analytics & SOQL through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Salesforce Analytics & SOQL 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 Salesforce Analytics & SOQL queries for multi-turn workflows
Salesforce Analytics & SOQL + LangChain Use Cases
Practical scenarios where LangChain combined with the Salesforce Analytics & SOQL MCP Server delivers measurable value.
RAG with live data: combine Salesforce Analytics & SOQL tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Salesforce Analytics & SOQL, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Salesforce Analytics & SOQL tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Salesforce Analytics & SOQL tool call, measure latency, and optimize your agent's performance
Salesforce Analytics & SOQL MCP Tools for LangChain (6)
These 6 tools become available when you connect Salesforce Analytics & SOQL to LangChain via MCP:
sf_get_dashboard
Each component includes its type, header, data values, and the source report. Dashboards provide pre-built visual summaries. Get the dashboard ID from sf_list_dashboards. Use when the user asks "show me the sales dashboard" or wants a visual summary of specific metrics. Get all component data from a specific Salesforce dashboard — charts, metrics, and tables with their underlying data
sf_list_dashboards
Returns dashboard title, folder, last referenced date, and dashboard ID. Dashboards contain visual components (charts, tables, metrics) built from reports. Use to find dashboard IDs before fetching their component data with sf_get_dashboard. List available Salesforce dashboards with title, folder, and last referenced date to discover visualization assets
sf_list_reports
Returns report name, folder path, report format (Tabular/Summary/Matrix), last run date, and report ID. Use when the user asks about available reports, wants to find a specific one, or needs report IDs before running them with sf_run_report. List available Salesforce reports with name, folder, format, and last run date to discover reporting assets
sf_record_count
Returns the total number of records. Use for quick data volume checks: "how many leads do we have?", "total number of accounts", or capacity planning. Accepts any standard or custom object API name. Get the total record count for any Salesforce object — Account, Contact, Lead, Opportunity, Case, or any custom object
sf_run_report
Get the report ID from sf_list_reports first. This is the read-only equivalent of clicking "Run Report" in the Salesforce UI. Returns up to 2000 rows. Use when the user asks for specific report data or wants to extract insights from a saved report. Execute a specific Salesforce report by ID and return its full data — all rows, columns, and groupings
sf_run_soql
This is the most powerful and flexible tool — you can query any standard or custom object, apply filters, use aggregate functions, and join related objects. Example: SELECT Id, Name, Amount, StageName FROM Opportunity WHERE StageName = 'Closed Won' AND Amount > 10000 LIMIT 10. Use when no other tool covers the specific data need, or when the user requests a custom query. Execute a raw SOQL query against your Salesforce org to retrieve any data from standard or custom objects
Example Prompts for Salesforce Analytics & SOQL in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Salesforce Analytics & SOQL immediately.
"What was our total revenue closed this quarter?"
"Show me all reports in the Sales folder"
"How many accounts do we have by industry?"
Troubleshooting Salesforce Analytics & SOQL MCP Server with LangChain
Common issues when connecting Salesforce Analytics & SOQL to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersSalesforce Analytics & SOQL + LangChain FAQ
Common questions about integrating Salesforce Analytics & SOQL 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 Salesforce Analytics & SOQL with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 Salesforce Analytics & SOQL to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.