ConfigCat MCP Server for LangChainGive LangChain instant access to 18 tools to Create Config, Create Environment, Create Segment, and more

Name: ConfigCat
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect ConfigCat through 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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The ConfigCat MCP Server for LangChain is a standout in the Ship It category — giving your AI agent 18 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

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VS Code

JetBrains

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+ other MCP clients

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

asyncio.run(main())

Fully ManagedVinkius Servers

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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 ConfigCat MCP Server

Connect ConfigCat to any AI agent to streamline your feature flag management and release workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with ConfigCat through native MCP adapters. Connect 18 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

Configurations & Environments — List, create, and manage configuration containers and environments (Test, Staging, Production) across your products.
Feature Flags & Settings — Create and inspect feature flags or settings (boolean, string, int, double) to control application logic.
Value Management — Retrieve and update setting values dynamically to trigger real-time changes in your software without redeploying.
Segment Control — Manage user segments to target specific groups for canary releases or A/B testing.

The ConfigCat MCP Server exposes 18 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 18 ConfigCat tools available for LangChain

When LangChain connects to ConfigCat through Vinkius, your AI agent gets direct access to every tool listed below — spanning feature-flags, remote-config, release-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create config on ConfigCat

Create a new configuration

create

Create environment on ConfigCat

Create a new environment

create

Create segment on ConfigCat

Create a new segment

create

Create setting on ConfigCat

Create a new feature flag or setting

delete

Delete config on ConfigCat

Delete a configuration

delete

Delete environment on ConfigCat

Delete an environment

delete

Delete segment on ConfigCat

Delete a segment

delete

Delete setting on ConfigCat

Delete a setting

get

Get config on ConfigCat

Get details of a specific configuration

get

Get environment on ConfigCat

Get details of an environment

get

Get segment on ConfigCat

Get details of a segment

get

Get setting on ConfigCat

Get details of a setting

get

Get setting value on ConfigCat

Get the value of a setting in an environment

list

List configs on ConfigCat

List all configurations in a product

list

List environments on ConfigCat

g., Test, Production) for a specific product. List all environments in a product

list

List segments on ConfigCat

List all segments in a product

list

List settings on ConfigCat

List all settings in a configuration

update

Update setting value on ConfigCat

Update the value/targeting of a setting

Connect ConfigCat to LangChain via MCP

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

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 18 tools from ConfigCat via MCP

Why Use LangChain with the ConfigCat MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine ConfigCat 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 ConfigCat queries for multi-turn workflows

ConfigCat + LangChain Use Cases

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

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

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

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

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

Example Prompts for ConfigCat in LangChain

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

"List all configurations for product ID 'prod_123'."

"Create a new boolean feature flag called 'Beta Feature' in config 'conf_abc'."

"Show me the details for environment 'env_987'."

Troubleshooting ConfigCat MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

ConfigCat + LangChain FAQ

Common questions about integrating ConfigCat 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.