> For the complete documentation index, see [llms.txt](https://docs.leadbay.app/doc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.leadbay.app/doc/leadbay-mcp/what-is-leadbay-mcp.md).

# What is Leadbay MCP?

**Leadbay MCP connects Claude to your Leadbay account, so you can work your leads by simply asking.**

Pull leads, qualify them, draft outreach, log activity — in plain language. Claude acts on your real data, with your permissions, just as you would in the app.

{% hint style="info" %}
**MCP** stands for *Model Context Protocol* — an open standard that lets AI assistants like Claude securely connect to external tools and data. The Leadbay MCP server is open source and lives at [github.com/leadbay/mcp](https://github.com/leadbay/mcp).
{% endhint %}

***

## Why connect Leadbay to Claude?

Instead of switching between the Leadbay app and your workflow, you work conversationally:

> *Pull today's top leads and tell me which two are worth opening this morning.*

> *Research acme.com — is it a fit for us?*

> *I just emailed Jane at Acme. Log it as outreach.*

Claude pulls the right companies, reasons over them, and replies with a short, qualified answer — then takes the follow-up action you ask for.

***

## Where it works

Leadbay MCP works with any AI assistant that supports the Model Context Protocol:

* **Claude Desktop**
* **Claude Cowork**
* **Claude Code**
* **Cursor**
* **Codex**

***

## See it in action

Ask in plain language — Claude replies with a ranked shortlist of qualified leads:

<figure><img src="/files/T4XvxV0dtTK10hClI0qb" alt="Claude returning a ranked table of qualified leads in chat"><figcaption><p>"Show me today's leads" — a ranked shortlist with fit score and the best contact.</p></figcaption></figure>

…then drafts the outreach for you:

<figure><img src="/files/89BDQssfRDi3JqOly8b3" alt="Claude drafting a personalized outreach email"><figcaption><p>"Draft an intro email" — ready-to-send variants in seconds.</p></figcaption></figure>

***

## Get started

Connect Leadbay to Claude and get to your first leads in about five minutes — no coding, no tokens to copy.

{% content-ref url="/pages/uch4ZQAkJqrspQ28ifMH" %}
[Quickstart](/doc/leadbay-mcp/quickstart.md)
{% endcontent-ref %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.leadbay.app/doc/leadbay-mcp/what-is-leadbay-mcp.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.