Supercharge your AI with Deterministic URL Engine. Stop breaking links. Parse and manipulate URIs reliably.

Q: Can I use the injectquery tool if the URL already has parameters?

Yes. The injectquery tool is built specifically to handle existing parameters, safely appending new ones using correct syntax whether it's the first parameter or the tenth.

Q: What should I use if I only need one piece of data from a query string?

Use extractquery. It lets you specify exactly which parameter key you want and pulls out just that value, keeping it clean and free of regex errors.

Q: Do I need to use parseurl before calling injectquery?

Not necessarily. injectquery can handle the structure itself. However, running parseurl first is smart practice; it lets you verify the link's existing components and build confidence in your data flow.

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.

Deterministic URL Engine provides flawless, programmatic control over web links. Stop fighting broken URLs. This MCP lets your AI client accurately parse complex URIs, extract specific tracking parameters from messy query strings, and inject new data points—all without risking double ampersands or malformed question marks.

What your AI can do

Extract query

Pulls a single parameter value from a URL's query string without using complex regular expressions.

Inject query

Updates or adds new parameters to a URL, guaranteeing perfect placement of question marks and ampersands.

Parse url

Breaks down any complex URL into its fundamental components: protocol, host, path, query string, and hash.

Structural URL Breakdown

Deconstructs any complete URL into its core parts: the protocol, host, path, query parameters, and hash tag.

Safe Parameter Injection

Adds or updates specific tracking parameters in a URL, ensuring mathematically correct addition of question marks and ampersands.

Targeted Query Extraction

Pulls the value for one specified parameter from a long query string without resorting to unreliable regular expressions.

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

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AI Agent

Deterministic URL Engine: 3 Tools

This set of tools gives your agent the power to break down complex URLs, pull specific data points from query strings, and safely build new web links.

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 Deterministic URL Engine on Vinkius

Extract Query

Pulls a single parameter value from a URL's query string without using complex regular expressions.

Inject Query

Updates or adds new parameters to a URL, guaranteeing perfect placement of question...

Parse Url

Breaks down any complex URL into its fundamental components: protocol, host, path...

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 Deterministic URL 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": {
  "deterministic-url-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 Deterministic URL 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:

"deterministic-url-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 Deterministic URL 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

Deterministic URL 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 url-parser. 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.

The tedious process of debugging web links:

Right now, if your agent tries to generate a link or modify one in conversation, it's a mess. You copy-paste the URL, tell your AI client what to change—say, adding `utm_source=email`—and then you spend five minutes checking if the resulting link has double question marks (`??`) or if the ampersands are misplaced. It’s manual QA for every single piece of web data.

With this MCP, that whole process vanishes. You let your agent use `inject_query`. You provide the base URL and the new parameter set; it guarantees correct syntax, regardless of what's already in the link. You get a clean, functional URL instantly.

The Deterministic URL Engine MCP provides structural certainty.

Before this, understanding a complex URL meant guessing which parts were which: Was that segment the path? The host? A query parameter? You had to break it down piece by piece in your head or with multiple separate commands. It’s guesswork.

Now you use `parse_url`. It gives you an atomic breakdown of every single component, separating protocol from pathname and isolating all parameters into one clean object. The data is structured the moment it enters the system.

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What your AI can actually do with this

When you're building any system that touches the internet—be it analytics, marketing funnels, or API calls—URL structure is everything. The problem is simple: standard LLMs are terrible at URL mechanics. They treat links like plain text and will mangle them when they try to add a tracking parameter or split a deep query string.

You end up with broken links that just don't work.

The Deterministic URL Engine fixes this by running all link manipulation through a reliable V8 engine. It handles the messy mechanics of web addresses so you don't have to worry about syntax errors, concatenation failures, or missing components. Instead of guessing how to split a path into its host and query parameters, your agent simply calls parse_url for an atomic breakdown.

Need to add a campaign tag? Use inject_query. It guarantees the link remains valid every time. This kind of reliable data plumbing is exactly what Vinkius provides in their catalog, letting you trust your AI client with mission-critical web links.

Built · Hosted · Managed by Vinkius Deterministic URL Engine MCP - Parse & Inject URLs

Server ID 019e3903-85e7-719e-99e5-ce0dde586eb4

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is, you get predictable, reliable web address mechanics every single time. No guesswork required.

You feed your agent a URL and specify what you need: maybe just the base host, or perhaps a new tracking tag.

Your AI client invokes the appropriate tool—for example, running parse_url to analyze structure, or extract_query to pull data.

The engine returns the clean, processed output (like the separated hostname or the newly modified link), ready for your next step.

What Changes When You Connect

Prevents broken marketing funnels: Use inject_query to safely add UTM tags, knowing the link will always validate correctly, saving you hours of QA time.

Accurate data extraction: Pull specific codes or tokens using extract_query without writing risky regex. It isolates exactly what you need from long query strings.

Structural integrity: Never guess how a URL is built again. Run parse_url to get the absolute breakdown of every component, making your agent's understanding rock solid.

Reliable API payloads: When building agents that interact with webhooks or endpoints, this MCP ensures the required parameters are formatted correctly before sending data.

Frictionless development: Developers gain a predictable layer for link manipulation. They don't have to build custom parser logic; they just call parse_url.

See it in action

01 01

Attribution Tracking Link Generation

A marketer needs to generate 50 unique links, each requiring a different campaign ID. Instead of manually checking the syntax for every link, they ask their agent to use inject_query five times, ensuring flawless parameter placement across all resulting URLs.

02 02

Deep Link Data Retrieval

A customer service bot receives a support ticket with a complex callback URL. It uses extract_query to pull out the specific 'ticket_id' and 'user_session' parameters, passing only that clean data to the backend system.

03 03

API Endpoint Normalization

A developer is writing a script that needs to know if an incoming URL points to a staging or production environment. They use parse_url first to check the hostname component, letting them route the request correctly.

04 04

Data Context Mining

An agent processes raw logs containing many URLs. It uses parse_url and then extract_query in sequence: first getting the base path, then pulling a specific 'user_id' from that path's query string.

The honest tradeoffs

Using simple string concatenation

Anti-pattern

Trying to manually add parameters like link + '?utm=source' when the link already contains a question mark, resulting in broken syntax like link??utm=source.

The Fix

Use inject_query. This tool handles the conditional logic for adding the first '?' or appending subsequent '&' symbols automatically. It’s built to prevent these specific concatenation errors.

Over-relying on Regex

Anti-pattern

Writing a complex regex pattern in your agent prompt to capture parameters like token from a URL, which fails if the parameter order changes or if the query string is empty.

The Fix

Use extract_query. This tool abstracts away the complexity of query string parsing. You just tell it the parameter key you want, and it pulls the value reliably.

Treating URL data as text

Anti-pattern

Passing a long web address to an agent without first checking its structure, leading the agent to miss crucial components like the protocol or the path.

The Fix

Always start with parse_url. This gives your agent the full context—protocol, host, and pathname separately—so it knows exactly what kind of link it's dealing with.

When It Fits, When It Doesn't

Use this MCP if you need to modify or deeply understand web links. Specifically, use parse_url when your goal is structural analysis (e.g., 'What is the host?'). Use extract_query when your goal is read-only data retrieval (e.g., 'Give me the value of the token parameter'). Only call inject_query when you absolutely must modify and guarantee a new, functional URL. Don't use this if you just need to check if a link exists; that requires external HTTP calls. If your problem is simply identifying the type of data in the link (e.g., 'Is this an internal or external link?'), basic string checks might suffice, but for anything requiring precision—like adding tracking codes—this MCP is mandatory.

Questions you might have

How does the Deterministic URL Engine MCP fix broken links? +

The engine uses a pristine V8 deterministic mechanism to handle all URI mechanics, eliminating common errors like double question marks or misplaced ampersands that manual LLM manipulation causes.

Can I use the inject_query tool if the URL already has parameters? +

Yes. The inject_query tool is built specifically to handle existing parameters, safely appending new ones using correct syntax whether it's the first parameter or the tenth.

What should I use if I only need one piece of data from a query string? +

Use extract_query. It lets you specify exactly which parameter key you want and pulls out just that value, keeping it clean and free of regex errors.

Do I need to use parse_url before calling inject_query? +

Not necessarily. inject_query can handle the structure itself. However, running parse_url first is smart practice; it lets you verify the link's existing components and build confidence in your data flow.

How does the `extract_query` tool handle sensitive data like authentication tokens within a URL? +

It securely extracts only the requested parameter value. You pass the key (e.g., 'token'), and it returns the clean value without manipulating or exposing the surrounding URI structure.

If I pass an invalid or malformed URI to `parse_url`, will the deterministic engine fail? +

No, the V8 engine is designed for resilience. It handles invalid inputs gracefully by returning nulls or partial data for components it can't parse, preventing a hard failure.

When using `inject_query`, can I inject multiple JSON key-value pairs in one request? +

Yes, you provide all new parameters within the single JSON string input. The engine processes them as a set of additions, guaranteeing correct separation with ampersands (&) for every pair.

Is there a performance difference between using `parse_url` and implementing URL logic manually with regex? +

Yes. Since it runs on a pure Javascript V8 deterministic engine, the processing is extremely fast. It avoids the overhead and complexity associated with custom code or bloated external packages.

Why use an MCP instead of letting the AI format the URL? +

AIs are probabilistic text generators, not web browsers. If a URL already has a ?, adding another parameter requires &. LLMs frequently guess the wrong delimiter, breaking critical affiliate tracking or API requests. The MCP guarantees correct serialization.

Can it extract multiple parameters? +

Yes! If you use the parse_url tool, it returns a queryParams JSON object containing every single key and value found in the URL. If you only want one, use extract_query.

Does this tool execute network requests? +

No. The entire engine executes pure algorithmic parsing on strings. It does not validate if the URL is active online, it merely processes its mathematical construction.

Connect to your AI in seconds.

Extract query

Inject query

Parse url

Deterministic URL Engine: 3 Tools

Make your AI actually useful.

Extract Query

Inject Query

Parse Url

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

The tedious process of debugging web links:

The Deterministic URL Engine MCP provides structural certainty.

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

Attribution Tracking Link Generation

Deep Link Data Retrieval

API Endpoint Normalization

Data Context Mining

The honest tradeoffs

Using simple string concatenation

Over-relying on Regex

Treating URL data as text

When It Fits, When It Doesn't

Questions you might have