ConfigCat MCP for AI Agents. Manage Feature Flags and Remote Configuration Values Across Environments

ConfigCat manages feature flags and remote configurations directly through your AI client. This MCP lets you list environments, create settings, toggle features, and update configuration values without touching code. It provides granular control over application logic in development, staging, and production.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Give Claude and any AI agent real-world access

View and organize system configurations

List all available product configurations, environments, and user segments to understand the current setup.

Manage core settings and flags

Create new feature flags or settings—whether they're boolean switches, strings, or numbers—and delete unused ones.

Dynamically adjust values in real-time

Retrieve the current value of any setting for a specific environment and update that value instantly to trigger immediate application changes.

Build user targeting groups

Define new user segments or view existing ones, allowing you to target feature rollouts to specific user groups.

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AI Agent

What AI agents can do with ConfigCat: 18 Tools for Configuration Management

These tools allow your agent to list, create, delete, retrieve, and update every element within your configuration system, from entire environments down to single feature flags.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using ConfigCat MCP

Create Config

Creates a brand new configuration container for your product.

Create Environment

Builds a dedicated environment (like QA or Production) to isolate testing.

Create Segment

Defines a new group of users for targeted testing or release management.

Create Setting

Adds a specific feature flag or setting (e.g., 'beta_checkout') to an existing...

Delete Config

Removes an entire product configuration container.

Delete Environment

Deletes a specific testing or live environment.

Delete Segment

Removes a predefined user segment from the system.

Delete Setting

Deletes an existing feature flag or setting key.

Get Config

Retrieves all details about a specific configuration container.

Get Environment

Gets detailed information on a specified environment instance.

Get Segment

Fetches the criteria and details of a specific user segment.

Get Setting

Retrieves metadata about a feature flag or setting key.

Get Setting Value

Checks the current value of a setting within a specific environment.

List Configs

Lists all configuration containers available for your product ID.

List Environments

Shows all existing environments (e.g., Test, Staging) tied to a product.

List Segments

Lists all defined user segments for the entire product.

List Settings

Shows every feature flag or setting key within a given configuration.

Update Setting Value

Changes the value of an existing setting, which triggers real-time behavior updates in your application.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

ConfigCat MCP for AI Agents MCP is compatible with Claude

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The ConfigCat MCP for AI Agents integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "configcat": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the ConfigCat MCP for AI Agents tools with full Vinkius guardrails applied.

ConfigCat MCP for AI Agents MCP is compatible with VS Code

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"configcat": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on each call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with ConfigCat, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,200+ others, all in one place
Add new capabilities to your AI anytime you want
Connections are secured and governed automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog weekly

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ConfigCat. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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ConfigCat MCP for AI Agents: Managing Feature Flags in Software Development

Today, changing a simple feature toggle often requires a full deployment cycle. You write the change, commit it, open a PR, wait for review, and then deploy across multiple environments—all just to see if one flag works correctly on Staging. This friction slows down every release.

With this MCP, you simply ask your agent to check or update flags. For instance, telling your agent to `get_setting_value` for a specific feature in the Test environment gives you instant confirmation. You gain control over your software's behavior without touching the build pipeline.

ConfigCat MCP for AI Agents: Controlling Environment Parity with Remote Configurations

Manually verifying that Production, Staging, and Test environments all have identical configurations is a tedious, error-prone chore. Engineers spend hours cross-referencing dashboards just to confirm one variable didn't get missed.

The ConfigCat MCP lets you automate this check. You can use `list_environments` and then instruct your agent to compare settings across multiple locations using `get_setting_value`. Now, configuration drift is a chat command away from detection.

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feature-flags

remote-config

release-management

toggles

configuration-management

What ConfigCat MCP for AI Agents MCP does for your AI

You shouldn't need to redeploy code every time a feature flag needs tweaking or an environment variable changes. ConfigCat gives developers and product teams the ability to manage all that complexity from chat alone. Using your AI client, you can list environments (like Test, Staging, Production) and instantly check specific setting values for any given configuration.

Need to turn on a beta feature? Your agent handles it: you call the necessary tools to create or update a setting value immediately. You can also define user segments, which is critical for running targeted A/B tests or canary releases. This capability means your release workflow moves at the speed of conversation, not the speed of CI/CD pipelines.

When you connect ConfigCat via Vinkius, your AI client gets access to this entire catalog of feature toggles and environment controls.

Built · Hosted · Managed by Vinkius ConfigCat MCP for AI Agents — Feature Flag Management

Server ID 019e387c-cd2f-73db-a339-12e91fd1fc2a

Vinkius Inspector

Compliance Grade A+

Score 98.33/100

Report View Report ↗

Who uses ConfigCat MCP for AI Agents MCP

This MCP is essential for developers who hate the friction of manual config management and DevOps engineers whose job relies on rapid, safe environment synchronization. If your team struggles with coordinating feature rollouts across multiple product versions or environments, this tool saves you hours.

DevOps Engineer

Managing environments using tools like list_environments and ensuring that configurations are synced correctly before a deployment.

Software Developer

Quickly toggling features or checking flag statuses directly from their IDE to test logic without needing a full build/deploy cycle.

Product Manager

Overseeing feature rollouts and user segments using simple chat commands, confirming that the right users see the new functionality at the right time.

Benefits of connecting ConfigCat MCP for AI Agents MCP

Control feature rollouts without code changes. Use update_setting_value to flip a switch, activating or deactivating features in production instantly.

Maintain environment parity across your product line. List all configurations using list_configs and verify that Staging matches Production before launch.

Target specific users for testing. Create new segments via create_segment so you can run A/B tests only on a small, controlled group of users.

Speed up debugging by verifying settings. You can check the exact state of any flag in any environment using get_setting_value, eliminating guesswork.

Streamline your release process. By managing environments and configurations with this MCP, you reduce reliance on manual deployment steps.

ConfigCat MCP for AI Agents MCP use cases

01 01

Testing a new payment flow for premium users

A product manager needs to test a paid feature only on paying customers. They use the agent to create_segment specifically for 'Premium Users' and then verify that the associated setting value is active for that group using get_setting_value.

02 02

Rolling back a broken checkout button

A developer realizes a new feature flag broke the site. Instead of deploying an emergency hotfix, they ask their agent to use update_setting_value to immediately set the problematic flag's value back to 'false'.

03 03

Setting up isolated staging testing

A DevOps engineer needs a clean test slate. They instruct their agent to create_environment for 'Pre-Prod QA', ensuring it has all necessary settings before the next major build.

ConfigCat MCP for AI Agents MCP tradeoffs

What to watch out for, and the recommended way to handle each one.

Treating config management as code

Avoid

When a flag needs to be changed, developers often treat it like a PR, requiring merging and deployment cycles. This is slow and introduces unnecessary risk.

Instead

Use the ConfigCat MCP's update_setting_value tool directly via your agent. This bypasses code deployment entirely, changing the feature state in real-time.

Confusing environments with configurations

Avoid

A user might try to list all settings across their entire product without knowing which container they are checking, leading to ambiguous results.

Instead

Always start by listing the available configuration containers using list_configs first. Then, specify the exact environment (like Staging) before asking your agent to check setting values.

When to use ConfigCat MCP for AI Agents MCP

Use this MCP if you need runtime control over application features and environmental settings. If your workflow requires toggling flags, updating variables, or running A/B tests without recompiling or redeploying code, this is for you. Don't use it if your primary goal is data storage or complex user authentication; for those, a dedicated database connector works better. Also, if you only need to read static documentation about settings, the get_setting tool will suffice, but you won't be able to modify anything.

Frequently asked questions about ConfigCat MCP for AI Agents MCP

How does the ConfigCat MCP help manage feature flags across different environments? +

The ConfigCat MCP lets you view and manipulate settings for multiple environments (Test, Staging, Production) from a single chat interface. You can check if the flag status is consistent everywhere, saving hours of manual cross-checking.

Can I use this with my AI client to run A/B tests? +

Yes. By managing user segments and dynamically updating setting values, you can easily target a small group (a segment) for an A/B test without affecting the general user base.

What if I need to delete a whole set of flags or settings? +

You have tools available to remove configuration containers, environments, and individual settings. This helps keep your product's configuration clean and prevents clutter from old features.

Does the ConfigCat MCP require me to write code for simple flag changes? +

No. The entire point of this connector is to manage these controls through natural conversation with your AI client, eliminating the need to commit code just to flip a switch.

Is ConfigCat MCP safe to use in production? How do I know it's secure? +

The tool allows you to get and update values for Production environments. Because all actions are logged and initiated through your AI client, you retain an audit trail of every change.

View all recipes →

Govern Feature Flags Across Tools Using MCP

127 feature flags in production and nobody knows which ones are safe to remove , your agent audits both platforms and tells you

Launchdarkly Configcat Airtable

View all recipes

Give Claude and any AI agent real-world access

What AI agents can do with ConfigCat: 18 Tools for Configuration Management

Create Config

Creates a brand new configuration container for your product.

Create Environment

Builds a dedicated environment (like QA or Production) to isolate testing.

Create Segment

Defines a new group of users for targeted testing or release management.

Create Setting

Adds a specific feature flag or setting (e.g., 'beta_checkout') to an existing...

Delete Config

Removes an entire product configuration container.

Delete Environment

Deletes a specific testing or live environment.

Delete Segment

Removes a predefined user segment from the system.

Delete Setting

Deletes an existing feature flag or setting key.

Get Config

Retrieves all details about a specific configuration container.

Get Environment

Gets detailed information on a specified environment instance.

Get Segment

Fetches the criteria and details of a specific user segment.

Get Setting

Retrieves metadata about a feature flag or setting key.

Get Setting Value

Checks the current value of a setting within a specific environment.

List Configs

Lists all configuration containers available for your product ID.

List Environments

Shows all existing environments (e.g., Test, Staging) tied to a product.

List Segments

Lists all defined user segments for the entire product.

List Settings

Shows every feature flag or setting key within a given configuration.

Update Setting Value

Changes the value of an existing setting, which triggers real-time behavior updates in your application.

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

ConfigCat MCP for AI Agents: Managing Feature Flags in Software Development

ConfigCat MCP for AI Agents: Controlling Environment Parity with Remote Configurations

feature-flags

remote-config

release-management

toggles

configuration-management