# Connectors

## Supported Connectors

For easier access, setup guides below describe how to access the MCP Server via a variety of common AI agent providers:

* [Claude](/integrations/agentic-ai/mcp-server/connectors/claude.md)

## Building MCP Clients

For cases where you are building your own MCP Client connector, access the MCP Server via the HTTPS transport scheme at `https://mcp.pending.ai/mcp`. Authentication is required for tool access and listing. It is recommended to use a framework that supports the OAuth2.0 authentication flow. Below shows a minimal example for using the Python [FastMCP](https://github.com/jlowin/fastmcp) package.

{% code title="FastMCP Example" %}

```python
from fastmcp import Client

async with Client("https://mcp.pending.ai/mcp", auth="oauth") as client:
    result = await client.list_tools()
```

{% endcode %}


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# Agent Instructions: 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:

```
GET https://docs.pending.ai/integrations/agentic-ai/mcp-server/connectors.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.