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Access and update CallRail call, text, and form data through MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "@kanopi/callrail-mcp" yet — see the docs or source repo.
Using the CallRail MCP tool, fetch call records from my account for the last 7 days and organize them in a table by source, call duration, and answered status.
A structured list or table of recent call data for reviewing call performance.
Read text messages from the CallRail account and list the latest 20 conversations with timestamp, contact, and message direction.
A summary of text conversations to quickly understand customer communications.
Use the CallRail MCP tool to read this month's form submissions and summarize submission count and top sources.
A summary of form submissions and source breakdown for lead analysis.
Marketers can use this tool to read calls, texts, and form data from CallRail in one place. It helps them understand lead sources and customer interactions more quickly.
Data analysts can extract call tracking and form submission records from a CallRail account for reporting and analysis. It is useful for measuring campaign performance or comparing sources.
Developers can connect this MCP server to MCP-compatible AI clients so models can read and write CallRail API v3 data directly. This is useful for automating customer communication workflows.
It is an MCP server for the CallRail API v3. It exposes call tracking, text messaging, form submissions, and related capabilities as MCP tools for reading and writing to your CallRail account.
Based on the description, it supports call tracking, text messages, form submissions, and more. For the exact tool surface, see the source repository.
The provided material does not include installation steps or prerequisites. Tools like this typically involve CallRail account access and an MCP runtime, so check the source repository for details.
Access CallRail data to manage call tracking, tags, users, and reports.
Send transactional emails, track status, and manage contacts through MCP.
Manage TestRail projects, cases, runs, and results using natural language.
Connect AI clients to retail customer, inventory, sales, order, and support workflows.
Enable AI agents to provision numbers, call, text, and manage credentials.
Manage TestRail testing workflows and turn Jira tickets into test cases.