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Pitchly MCP Server for LangChainGive LangChain instant access to 11 tools to Create Record, Delete Record, Get Record Details, and more

Built by Vinkius GDPR 11 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Pitchly 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 App Connector for LangChain

The Pitchly app connector for LangChain is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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({
        "pitchly": {
            "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 Pitchly, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Pitchly
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 Pitchly MCP Server

Connect your Pitchly account to any AI agent and take full control of your organizational experience and content orchestration through natural conversation. Pitchly is the data management platform of choice for professional services firms, and this integration allows you to retrieve workspace metadata, manage custom data tables, and update critical records (deals, bios, tombstones) directly from your chat interface.

LangChain's ecosystem of 500+ components combines seamlessly with Pitchly through native MCP adapters. Connect 11 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

  • Workspace & Table Orchestration — List all managed workspaces and retrieve detailed table structures programmatically to ensure your data foundation is always synchronized.
  • Record Lifecycle Management — Query, create, and update records across custom tables with detailed profile metadata directly from the AI interface to maintain high-fidelity business intelligence.
  • Content Discovery Intelligence — Search through complex data sets for specific deals, professional bios, or tombstone data via natural language to drive better research efficiency.
  • Data Ingestion Control — Automate the creation of new records and manage organizational metadata using simple AI commands.
  • Operational Monitoring — Track system responses and manage workspace health to ensure your experience management is always optimized.

The Pitchly MCP Server exposes 11 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.

All 11 Pitchly tools available for LangChain

When LangChain connects to Pitchly through Vinkius, your AI agent gets direct access to every tool listed below — spanning experience-data, professional-services, content-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_record

Add a new record to a table

delete_record

Delete a record from a table

get_record_details

Get details of a specific record

get_table_details

Get details of a specific table

get_workspace_details

Get details of a specific workspace

list_fields

List all fields in a table

list_table_records

List records in a Pitchly table

list_tables

List tables in a workspace

list_workspaces

List all Pitchly workspaces

search_records

Search records within a table

update_record

Update an existing record

Connect Pitchly to LangChain via MCP

Follow these steps to wire Pitchly into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 11 tools from Pitchly via MCP

Why Use LangChain with the Pitchly MCP Server

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

01

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

02

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

03

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

04

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

Pitchly + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Pitchly in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Pitchly immediately.

01

"List all tables in my 'Corporate' workspace in Pitchly."

02

"Show me all records in the Client Engagements table that were updated this week."

03

"Create a new record in the Deal Pipeline table for the ScaleUp Technologies opportunity."

Troubleshooting Pitchly MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Pitchly + LangChain FAQ

Common questions about integrating Pitchly MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.