> ## Documentation Index
> Fetch the complete documentation index at: https://docs.corvic.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent MCP

> Talk to a deployed Corvic agent from any MCP-compatible client.

**Agent MCP** lets you connect to a single deployed agent from your own tools — ask it questions, retrieve the cited resources behind its answers, and trigger sync/deploy. It works with any MCP-compatible client: Claude, Cursor, agent frameworks, or a custom client of your own.

For access to a whole room — pipelines, memories, lenses, and data — use [Room MCP](https://docs.corvic.ai/mcp-connect/room-tools.md) instead.

## Get connected

Open your agent's **Integration & Sharing → Integration** tab and copy its **MCP URL** and **Access Token**. See [Agents](https://docs.corvic.ai/features/agents.md#mcp-integration).

Configure your MCP client with that URL and send the token as a Bearer header:

| | Value |
| - | - |
| **MCP URL** | From the agent's Integration tab |
| **Auth** | `Authorization: Bearer <ACCESS_TOKEN>` |

> [!WARNING]
>
> Treat access tokens like passwords. Don't commit them to source control — load them from environment variables or a secrets manager.

> [!TIP]
>
> The room's **MCP Playground** is the fastest way to explore before wiring a client up: it lists every tool with its input schema and lets you call them live, showing the exact requests and raw responses an MCP client would see.

## Available tools

| Tool | Description |
| - | - |
| `query` | Ask the agent a question and get its grounded answer, optionally with citations (`with_citation: true`). |
| `get_resource_download_url` | Get download URLs for resource IDs — typically the citations returned by `query`. |
| `get_resources` | Look up resources by their original file paths. |
| `sync_agent_data_app` | Sync the agent's workflow to pick up the latest data. |
| `deploy_agent` | Deploy the agent to apply the latest changes. |

Your client's tool listing always reflects the live set — descriptions and input schemas come straight from the agent.

## A typical exchange

**1. Ask**

Call `query` with your question and `with_citation: true`. The agent answers from its configured knowledge, citing the rows and documents it used.

**2. Follow the citations**

Pass the cited resource IDs to `get_resource_download_url` to fetch the underlying documents.

**3. Keep it fresh**

After new data lands, call `sync_agent_data_app` and then `deploy_agent` so the agent answers from the latest state.

## Related

> [card] [MCP Connect](https://docs.corvic.ai/mcp-connect/overview.md)
>
> Agent vs. room access and credentials.

> [card] [Room tools](https://docs.corvic.ai/mcp-connect/room-tools.md)
>
> The full room surface: pipelines, memories, lenses, agents, and data access.

> [card] [Agents](https://docs.corvic.ai/features/agents.md)
>
> Configure and deploy the agent behind this endpoint.

> [card] [Sharing](https://docs.corvic.ai/features/sharing.md)
>
> Share chats and artifacts without an integration.


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