Vinkius
Marchex

Find campaign failures by tracing a single phone call.
Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Marchex MCP on Cursor AI Code Editor MCP ClientMarchex MCP on Claude Desktop App MCP IntegrationMarchex MCP on OpenAI Agents SDK MCP CompatibleMarchex MCP on Visual Studio Code MCP Extension ClientMarchex MCP on GitHub Copilot AI Agent MCP IntegrationMarchex MCP on Google Gemini AI MCP IntegrationMarchex MCP on Lovable AI Development MCP ClientMarchex MCP on Mistral AI Agents MCP CompatibleMarchex MCP on Amazon AWS Bedrock MCP Support

Connect to your AI in seconds.

Marchex MCP Server connects your AI client to Marchex's conversation intelligence platform. Use it to search call records, analyze performance metrics, and manage campaign data.

Your agent can list accounts, find specific calls using `search_calls`, retrieve granular call details via `get_call_details`, and calculate overall campaign health with `get_call_analytics`.

What your AI can do

Get account details

Retrieves detailed information for a single specified user or organizational account.

Get call analytics

Calculates and returns aggregated call performance metrics across a given time period.

Get call details

Fetches all available metadata for one specific, identified phone call record.

+ 7 more capabilities included
Search & Retrieve Call Records

Find specific call instances using timeframes or phone numbers with search_calls, then fetch complete metadata on any single call via get_call_details.

Analyze Campaign Performance

List all active campaigns (list_campaigns) and run deep analyses to get aggregated performance metrics using get_call_analytics.

Manage Phone Numbers & Accounts

See what numbers are available with list_numbers, check specific account details with get_account_details, or list all user accounts with list_accounts.

Inspect Campaign Configuration

View the setup and configuration of any tracking campaign using get_campaign_details.

List Users and Numbers

Get a list of all registered users (list_users) or check details on specific tracking phone numbers with get_number_details.

Compatible AI Apps

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ any other MCP app
Included with Plan

Waiting for input…

AI Agent

Marchex MCP Server: 10 Tools for Conversation Intelligence

Use these tools in your agent to get granular access to Marchex data. You can list accounts, search calls, retrieve analytics, and manage campaign configurations all from one chat interface.

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 Marchex on Vinkius

Get Account Details

Retrieves detailed information for a single specified user or organizational account.

Get Call Analytics

Calculates and returns aggregated call performance metrics across a given time...

Get Call Details

Fetches all available metadata for one specific, identified phone call record.

Get Campaign Details

Retrieves the full configuration and status details for a single tracking campaign.

Get Number Details

Gets specific operational information about one registered phone number.

List Accounts

Returns a list of all user accounts associated with the Marchex system.

List Campaigns

Lists every active and inactive tracking campaign setup in your account.

List Numbers

Returns a list of all phone numbers that can be used for tracking calls.

List Users

Generates a simple listing of all user accounts associated with the platform.

Search Calls

Searches through your entire call history using criteria like date range or phone...

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

Claude AI

1

Open Claude Settings

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

2

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.

3

Start a conversation

Open a new chat. The Marchex integration is available immediately — no restart needed.

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 Marchex, 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
Marchex 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 Marchex. 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 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Trying to figure out why a campaign failed always feels like digging through old spreadsheets.

Today, diagnosing a failure means jumping into the Marchex dashboard. You pull up the 'Campaign Performance' tab, get a vague number for 'calls missed,' then you copy that ID over to a spreadsheet to cross-reference it with call records from another system, hoping the fields align.

With this MCP server, your agent handles all those jumps. Instead of copying and pasting data between three different views, you just ask: 'Why did Campaign X fail?' The agent runs `get_campaign_details`, finds the necessary IDs, executes `search_calls`, and gives you a direct answer.

Marchex MCP Server lets you get precise call metrics.

You used to have to run separate reports for 'total calls' versus 'average duration.' This meant running two distinct queries, manually comparing the results in a spreadsheet, and risking mismatched date ranges every time.

Now, you ask your agent to calculate call analytics. It runs `get_call_analytics` in one go. You get the total count and average duration in one clean block of data. That's the difference.

What your AI can actually do with this

Marchex MCP Server gives your AI client full control over conversation intelligence. You can analyze call outcomes and track marketing performance by having your agent interact directly with Marchex's data using specific tools.

Searching and Retrieving Call Records
Your agent uses search_calls to pull through entire call histories, letting you narrow down records based on criteria like date ranges or phone numbers. Once you find a potentially relevant record, it fetches all available metadata for that single call via get_call_details. This pair of tools lets your client drill deep into specific conversations and get the full picture of what happened.

Analyzing Campaign Performance
To understand how campaigns are doing, your agent first runs through all active and inactive tracking campaign setups by calling list_campaigns. If you need to know exactly how a particular campaign is configured or if its status changed, it uses get_campaign_details for that specific setup. For the big picture, get_call_analytics calculates and returns aggregated call performance metrics across any given time period, giving you an overall view of campaign health.

Managing Phone Numbers and Accounts
Your client handles everything related to infrastructure management. It starts by listing every phone number that can be used for tracking calls using list_numbers. When you need specific operational details on one of those numbers—like its current status or associated metadata—it pulls that info with get_number_details.

For the user side, your agent can generate a simple listing of all users associated with the platform via list_users, and it also has access to list_accounts to return a list of every user account linked to Marchex. When you need deep insight into an individual organization or user's details, it runs get_account_details.

Putting It All Together
Your agent handles the entire lifecycle flow. You can check campaign setups with get_campaign_details and then use that context to run broad performance reports using get_call_analytics. The system maintains a clear separation between user management (list_users, list_accounts) and number/system management (list_numbers, get_number_details). Your AI client doesn't require you to jump through multiple dashboards; it just takes your natural language request—like, “What were the metrics for Q3?” or “Find me all calls from last Friday using this number”—and executes the precise sequence of tool calls needed to get the data.

It’s direct. It’s immediate.

Built · Hosted · Managed by Vinkius Marchex MCP Server - Call & Campaign Performance Tracking
Server ID 019d75ce-fe6a-7109-849f-bfd0545d34a2
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I use get_call_analytics? +

You tell your agent which time frame you want metrics for. The server runs get_call_analytics and gives you aggregate numbers like total calls or average duration.

What is the difference between list_campaigns and get_campaign_details? +

list_campaigns just spits out a roster of all campaign names. You must use get_campaign_details next, providing the specific ID, to see its actual setup.

Can search_calls find calls from last year? +

Yes, as long as you specify a date range that includes those records. You need to provide enough context (date/number) for search_calls to work.

Do I need get_account_details before searching calls? +

No, but it's good practice. If you run get_account_details, your agent knows which account scope to limit the search to when running search_calls.

How do I handle authentication when running list_accounts? +

You must provide your Marchex Client ID and Secret credentials. The server uses these to authenticate your AI client against the platform, ensuring secure access before listing accounts.

What specific metadata does get_call_details return for a single call? +

It returns detailed records including the caller's number, connection duration, final status (e.g., answered, busy), and which campaign triggered the call.

If I run many searches, how does the server handle rate limiting for search_calls? +

The Vinkius platform manages standard API rate limits. We recommend your agent implements smart retry logic or groups related calls into fewer, larger batches to avoid throttling.

What error message should I expect if the ID used in get_campaign_details is invalid? +

You'll receive a clear API error (likely 404) stating that the specified resource does not exist. This lets your agent recognize bad input and adjust its workflow without crashing.

How do I find my Marchex Client ID and Secret? +

Log in to the Marchex Developer Console and create an application to receive your credentials.

What call data can I access? +

You can access call metadata, duration, caller info, status, and aggregated performance metrics.

Is my integration secure? +

Absolutely. Your credentials are encrypted at rest and injected securely at runtime.

Built & Managed by Vinkius 30s setup 10 tools

We've already built the connector for Marchex. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 10 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.

Zero hosting required Full MCP catalog included Enterprise-grade security Auto-updated by Vinkius

Built, hosted, and secured by Vinkius. You just connect and go.