Supercharge your AI with String Operations Engine. Get accurate character counts and format code strings.

Q: How do I check if a long article title is suitable for an SEO slug using changecasing?

Use changecasing and set the format to 'slugify'. The tool will convert messy characters, spaces, and capitalization into a clean, hyphenated URL string instantly.

Q: Can I use gettextstats to check character limits for database fields?

Yes. Run gettextstats on the text data you plan to insert. It returns the exact character count, letting you verify if the string fits before it hits the database layer.

Q: What happens if I use truncatetext with an empty string?

If you provide an empty input string, truncatetext will return an empty string. It's designed to be predictable even when the source data is null or empty.

Q: Is String Operations Engine reliable for coding variables?

Yes. The server executes pure JavaScript logic via changecasing, which is deterministic and accurate for converting strings into standard formats like camelCase, making it perfect for code generation tasks.

Q: Does changecasing correctly handle non-Latin or Unicode characters?

Yes, because it relies on a pure JavaScript core, 'changecasing' handles complex Unicode character sets. You can safely convert titles containing accents (like é) into standard programmatic formats.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

The String Operations Engine gives your AI deterministic control over text formatting. It calculates exact word and character counts, converts messy strings into precise programming casings (camelCase, slugify), and safely truncates large blocks of text.

Stop relying on LLMs to guess metrics; use this server for reliable, programmatic string manipulation.

What your AI can do

Change casing

Converts text into specific programming casings like camelCase, PascalCase, snake_case, kebab-case, or URL slugs.

Get text stats

Calculates the exact word count, character count, and line count for any provided text.

Truncate text

Safely cuts a string to a specified length, optionally appending a suffix like '...'.

Format programmatically

Converts any arbitrary string into standard development casings (e.g., camelCase, snake_case) using the change_casing tool.

Measure text dimensions

Calculates precise word, character, and line counts for a given block of text with the get_text_stats tool.

Safely shorten strings

Truncates long text fields to a specified length using the truncate_text tool, allowing you to append an optional suffix.

Ask an AI about this

Compatible AI Apps

OAuth 2.0 Compatible

Claude

ChatGPT

Cursor

Gemini

VS Code

JetBrains

Vercel

Zendesk

+ any other MCP app

Included with Plan

Waiting for input…

AI Agent

String Operations Engine: 3 Tools for Text Manipulation

Use these tools to gain deterministic control over text formatting. Change casing, calculate exact metrics, or safely cut strings with guaranteed results.

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 String Operations Engine on Vinkius

Change Casing

Converts text into specific programming casings like camelCase, PascalCase, snake_case, kebab-case, or URL slugs.

Get Text Stats

Calculates the exact word count, character count, and line count for any provided...

Truncate Text

Safely cuts a string to a specified length, optionally appending a suffix like '...'.

Connect to your AI in seconds. 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.

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 String Operations Engine 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": {
  "string-operations-engine": {
    "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 String Operations Engine tools with full Vinkius guardrails applied.

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:

"string-operations-engine": {
  "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 every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with String Operations Engine, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,000+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

String Operations Engine MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by string-ops. 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.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Text formatting shouldn't require a dozen copy/paste steps.

Today, if you write technical content or work on SEO, you manually check lengths. You paste the meta description into an online checker for char counts. Then, you take the title and run it through another tool just to get a clean URL slug. It's a messy sequence of tabs, copies, and manual checks.

With the String Operations Engine, your agent handles this flow automatically. You give the article title, and the system runs `change_casing` (slugify) and then uses `get_text_stats` to confirm the output length—all in one call. The result is clean code, verified metrics, and zero manual effort.

String Operations Engine: Format text casings & counts

Previously, if you needed to convert a variable name like 'user profile settings' into `userProfileSettings` for a component, you were stuck writing complex formatting rules in your own code. If the format changed (e.g., from camelCase to PascalCase), you had to rewrite it.

Now, simply ask the agent to run `change_casing`. It handles the specific programming logic and returns the correct string instantly. You just specify what casing you want; the tool does the rest.

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What your AI can actually do with this

Listen up. Large Language Models are great for spitting out natural-sounding text, sure. But when you need strict rules—like knowing exactly how many characters a headline has to be or converting a messy title into clean code—they fall apart. They guess metrics; they mess up casings. That's a huge headache whether you're building an API endpoint or optimizing for SEO limits.

The String Operations Engine fixes that crap by giving your AI client deterministic control over text formatting. You stop relying on LLMs to just guess the numbers; you use this server for reliable, programmatic string manipulation.

This MCP Server handles all the mechanical parts of text processing: counting, converting, and cutting. It runs these strict tasks through a dedicated core, so you get predictable results every single time. Here's how it works:

Format programmatically: You can convert any garbage string into standard development casings using the change_casing tool. Need it in camelCase, maybe PascalCase, or maybe you gotta make some URL-friendly slugs? Just run it through this server. It handles all those common formats like snake_case and kebab-case. The change_casing tool takes whatever messy text you throw at it and spits out clean, perfectly cased results.

Measure text dimensions: When you need to know the exact count—the word count, the character count, or how many lines a block of copy spans—you use the get_text_stats tool. It calculates these figures precisely for any input text. You get the real numbers for words, characters, and line breaks without fail.

Safely shorten strings: If you've got huge blocks of text that need to be cut down but you don't wanna lose all context or break the data structure, the truncate_text tool is your man. It safely cuts a string right down to the length you specify. You can even tell it to tack on an optional suffix, like '...', so people know they ain't reading the whole thing.

You use get_text_stats to get 100% accurate word counts, character counts, and line counts for any text you provide.

You use change_casing to convert messy input into standard formats like camelCase, PascalCase, or URL-friendly slugs, guaranteeing correct programming casings every time.

You use truncate_text to cut strings to an exact length while preserving data integrity. You can even specify a suffix to append when it cuts the text.

This engine gives your AI client absolute control over string manipulation. It's pure utility for anyone—developers, content teams, or anyone who needs metrics that actually add up. Because this stuff runs locally, your sensitive text never leaves your machine.

Built · Hosted · Managed by Vinkius String Operations Engine - Format Text & Count Characters

Server ID 019e38f5-7410-736a-8028-131556a0a5e0

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is: you get reliable, predictable text metrics and formatting without relying on the AI model's internal guesswork.

Provide the raw text and specify the required operation (e.g., 'count words' or 'convert to slug') to your AI client.

Your agent routes the request through the appropriate tool—get_text_stats, change_casing, or truncate_text.

The server executes the pure JavaScript function and returns a precise, measurable result (e.g., '142 characters' or 'userAccountName').

Who is this actually for?

This server is for developers and technical writers who hit a wall with basic LLM outputs. If your job involves writing code variables, managing SEO metadata, or dealing with database field limits, you need this. It's for the person tired of having to copy-paste text into three separate online tools just to check character counts.

Frontend Developer

Uses change_casing to convert user input strings into valid component property names (like React's camelCase) before rendering them.

SEO Specialist

Runs the meta description through get_text_stats to ensure it stays within the 160-character limit and checks word count for optimal reading flow.

DevOps Engineer

Uses truncate_text when preparing configuration files or database entries that have strict length constraints, ensuring data integrity.

What Changes When You Connect

Never guess metrics again. Use get_text_stats to get 100% exact word, character, and line counts. This is perfect for validating Twitter limits or SEO meta descriptions where accuracy matters.

Keep your code clean. The change_casing tool guarantees you can convert any text into proper formats—like converting 'user profile name' to a valid camelCase variable name.

Prevent data loss on input. If an API field has a 255-character limit, use truncate_text first. You control the cutoff point and can add a clean ellipsis suffix.

Run locally for privacy. Since this server executes pure JavaScript code client-side, your proprietary text never leaves your machine or hits an external API.

Process complex variables. The engine handles multiple casing formats—from snake_case for Python to kebab-case for URLs—so you don't need separate scripts for every language.

See it in action

01 01

Optimizing SEO Meta Descriptions

A content manager writes a meta description, but they aren't sure if it hits the 160-character limit. They ask their agent to run get_text_stats. The tool returns that the text is 158 characters long and contains exactly 24 words, confirming it fits perfectly without needing manual checks.

02 02

Building a React Component Library

A developer has user-provided labels like 'product details view'. They need this to become a valid component prop name. Instead of guessing or using messy regex, they run the text through change_casing (format='camelcase'), which reliably returns 'productDetailsView'.

03 03

Sanitizing Database Inputs

A user submits a massive bio field that exceeds the 500-character limit of the database. Before saving, the agent passes it to truncate_text with length=500 and suffix='...', ensuring the data fits while still marking where the cutoff happened.

04 04

Creating Clean URLs from Titles

A technical writer has an article title like '2024 Guide to Advanced Web Development!'. To make it a clean URL slug, they use change_casing (format='slugify'). The tool returns the perfect '2024-guide-to-advanced-web-development'.

The honest tradeoffs

Asking AI to count characters directly

Anti-pattern

Prompting an agent: 'How many characters are in this description?' The agent might respond with a guess or miscalculate, especially if the text contains complex Unicode characters.

The Fix

Don't ask. Run get_text_stats on the text instead. This tool provides deterministic metrics, guaranteeing accurate character counts regardless of complexity.

Trying to lowercase everything manually

Anti-pattern

Writing a script that needs to convert 'Product NAME' into a database column name like product_name. Doing this with simple string methods often misses edge cases.

The Fix

Use change_casing and specify the desired format (snake_case). It handles the conversion logic reliably, saving you from writing complex formatting code.

Using LLMs for truncation

Anti-pattern

Feeding a long text to an AI agent and asking it to 'shorten this.' The model might summarize or lose key information while trying to make the output sound natural.

The Fix

Use truncate_text. This function cuts the string at a precise character count, preserving all original characters up to that point. It's for hard limits, not summaries.

When It Fits, When It Doesn't

You should use this server if your primary need is absolute precision over text structure or measurement. For example, if you must validate a Twitter bio length (use get_text_stats), convert user input into a specific variable format (use change_casing), or ensure data fits a database column limit (use truncate_text).

Don't use this server if your goal is creative writing, summarizing an article, or adjusting the tone. For those tasks, you need a general-purpose LLM. The String Operations Engine isn't for making text sound better; it's for making text act correctly in code and data pipelines. If you can get away with 'good enough,' don't use this server. If your system fails because of one misplaced character or an incorrect casing, this is what you need.

Questions you might have

How do I check if a long article title is suitable for an SEO slug using change_casing? +

Use change_casing and set the format to 'slugify'. The tool will convert messy characters, spaces, and capitalization into a clean, hyphenated URL string instantly.

Can I use get_text_stats to check character limits for database fields? +

Yes. Run get_text_stats on the text data you plan to insert. It returns the exact character count, letting you verify if the string fits before it hits the database layer.

What happens if I use truncate_text with an empty string? +

If you provide an empty input string, truncate_text will return an empty string. It's designed to be predictable even when the source data is null or empty.

Is String Operations Engine reliable for coding variables? +

Yes. The server executes pure JavaScript logic via change_casing, which is deterministic and accurate for converting strings into standard formats like camelCase, making it perfect for code generation tasks.

Does using get_text_stats send my private content to an external server? +

No, it runs entirely locally on your machine. This tool makes zero API calls and processes text data within your environment. Your proprietary information never leaves your client's memory.

What happens if I give change_casing a non-string value? +

It throws a standard runtime error because the tool expects only string input. You must ensure the data you pass is text before calling 'change_casing' to prevent execution failure.

Are there any performance or rate limit concerns when using truncate_text many times? +

Since this engine runs locally, it doesn't adhere to external API rate limits. Performance is limited only by your client machine's CPU speed and the sheer volume of text you are processing.

Does change_casing correctly handle non-Latin or Unicode characters? +

Yes, because it relies on a pure JavaScript core, 'change_casing' handles complex Unicode character sets. You can safely convert titles containing accents (like é) into standard programmatic formats.

Why use an MCP just to count words? +

Because LLMs process tokens, not individual letters or words. If you ask an LLM to generate exactly 250 characters, it will guess and often fail. This MCP provides a deterministic mathematical check to guarantee exact limits.

Does the slugify tool handle international accents? +

Yes! The slugify logic decomposes strings (NFD normalization) to strip out all diacritics (like á, ö, ç) before converting spaces to hyphens and removing non-alphanumeric characters.

Does it require internet access? +

No. The entire engine executes purely on local JavaScript without any API requests, guaranteeing total privacy for your source code and content.

Connect to your AI in seconds.

Change casing

Get text stats

Truncate text

String Operations Engine: 3 Tools for Text Manipulation

Make your AI actually useful.

Change Casing

Get Text Stats

Truncate Text

Connect to your AI in seconds. 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

Works with Claude, ChatGPT, Cursor, and more

Text formatting shouldn't require a dozen copy/paste steps.

String Operations Engine: Format text casings & counts

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Optimizing SEO Meta Descriptions

Building a React Component Library

Sanitizing Database Inputs

Creating Clean URLs from Titles

The honest tradeoffs

Asking AI to count characters directly

Trying to lowercase everything manually

Using LLMs for truncation

When It Fits, When It Doesn't

Questions you might have