# Reply.io

> Use this tool when you need to automate multichannel sales outreach and analyze performance metrics. Reply.io integrates with AI models to manage sequences, enroll contacts, and control campaigns through natural language, solving problems like manual outreach and data analysis. It's ideal for B2B sales teams looking to optimize their outreach workflows and diagnose performance issues without switching between tools.

Canonical page: https://skillsregistry.net/skills/replyio-replyio  
JSON: https://api.skillsregistry.net/v1/skills/replyio-replyio

## Description

Reply.io is a sales engagement platform used by thousands of B2B sales teams to automate multichannel outreach — email, LinkedIn, calls, SMS, and WhatsApp. The Reply.io MCP server exposes the platform's core functionality as tools that any MCP-compatible AI model can call directly.

Once connected, your AI assistant can list and manage sequences, pull real-time performance analytics (delivery, open, reply, and click rates at the sequence and step level), enroll contacts, and control campaign state — all through natural language, no browser required.

Typical use cases:
- Ask Claude or Cursor to pull open and reply rates for your active sequences and identify underperformers
- Enroll a new contact in a sequence mid-conversation, without switching to the Reply.io dashboard
- Pause or start sequences, then check step-level stats to diagnose drop-off points
- Build AI agents that automate outreach workflows end-to-end — prospect, enroll, follow up, analyze

The MCP server is hosted by Reply.io and authenticated via API key. No self-hosting or open-source setup is required.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** browser-automation
- **Updated:** 2026-05-14

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/replyio/replyio)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "replyio-replyio"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/replyio-replyio` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/replyio-replyio/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt