> For the complete documentation index, see [llms.txt](https://docs.awenetwork.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.awenetwork.ai/awe-ecosystem/awe-service-via-open-mcp-ecosystem-awesome/mcp-overview.md).

# MCP Overview

### What is MCP?

[MCP](https://modelcontextprotocol.io/docs/getting-started/intro) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.

[MCP Overview](https://modelcontextprotocol.io/overview)\
[Dev Roadmap](https://modelcontextprotocol.io/development/roadmap)

### What is AWESOME MCP Platform

Together, these unlock a complete environment for worldbuilders, AI engineers, and creators to experiment, deploy, and scale autonomous systems — powered entirely by on-chain incentives.

[AWESOME MCP](https://www.awenetwork.ai/blog/awesome)

### How does AWESOME work?

{% content-ref url="/pages/TFN1bF19zeCPk6nTybMI" %}
[MCP Workflow Builder](/awe-ecosystem/awe-service-via-open-mcp-ecosystem-awesome/mcp-workflow-builder.md)
{% endcontent-ref %}

{% content-ref url="/pages/7hYcONCbUay8svCaVAYn" %}
[Agent Marketplace](/awe-ecosystem/awe-service-via-open-mcp-ecosystem-awesome/agent-marketplace.md)
{% endcontent-ref %}

### Featured Use Case

{% content-ref url="/pages/cB07ZL9pMDC0y7qVysrn" %}
[AWESOME X Agent](/awe-ecosystem/awe-service-via-open-mcp-ecosystem-awesome/awesome-x-agent.md)
{% endcontent-ref %}


---

# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.awenetwork.ai/awe-ecosystem/awe-service-via-open-mcp-ecosystem-awesome/mcp-overview.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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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.