# Quickstart

This guide connects Memco to your AI agent. By the end, your agent will be able to search shared knowledge, contribute new memories, and provide feedback.

## Prerequisites

You need a Memco account. If you do not have one, [sign up at memco.ai](https://memco.ai) to create one.

## Connect your coding agent

The fastest way to connect Memco to a coding agent is through the Memco plugin marketplace.

### Claude Code

Run inside Claude Code:

```
/plugin marketplace add memcoai/marketplace
/plugin install shared-memory@memco
```

### Codex

```
codex plugin marketplace add memcoai/marketplace
codex plugin add shared-memory@memco
```

Or run `codex` and open `/plugins` to browse and install interactively.

### Cursor

1. Open **Dashboard → Settings → Plugins**.
2. Under **Team Marketplaces**, choose **Add Marketplace → Import from Repo** and point it at `memcoai/marketplace`.
3. Reload Cursor (**Developer: Reload Window**).
4. Open the marketplace panel and install **memco-shared-memory**.

The plugin handles everything: it registers the Memco MCP server with your agent and provides the instructions your agent needs to use it. There is no need to separately configure an MCP connection or add agent instructions.

## Connect your AI assistant

If you use Memco with a general-purpose AI assistant — Claude Desktop, Claude on the web, Cowork, ChatGPT, Grok, or similar — you need to do two things: add the Memco Shared Memory MCP server, and instruct your agent to use it.

### Step 1: Add the MCP server

Add the Memco Shared Memory MCP server through your assistant's MCP or integrations settings. In Claude, this is under **Settings → Connectors**. In ChatGPT, look for **Plugins → MCPs** under settings. The endpoint is:

```
https://spark.memco.ai/mcp
```

Authentication is handled via OAuth. You will be redirected to sign in the first time you connect.

### Step 2: Instruct your agent to use it

Adding the MCP server makes the tools available, but your agent also needs to know it should use them. Add the following to your project instructions, custom instructions, or system prompt:

```
You have access to a shared memory server through the Memco Shared Memory
MCP server. Use that to look for findings others have shared, and to save
useful knowledge with other members of the team.
```

This tells the agent to search Memco for relevant knowledge before answering, and to save useful findings back for the rest of the team.

Where to put this depends on your assistant:

- **Claude** — add to your project instructions, or to **Settings → Profile → User preferences** for it to apply across all conversations
- **ChatGPT** — add to **Personalization → Custom Instructions**
- **Grok** — add to your system prompt or custom instructions

In the first few sessions, Memco is mostly listening. After a few days of use, you will start to notice your agent surfacing knowledge from previous sessions and from your teammates' work.

## Connect via MCP directly

If your agent does not support the plugin marketplace, you can configure the MCP connection manually. This requires two steps: adding the Memco MCP server to your agent's configuration, and instructing your agent to use it (for example, in your project's `AGENTS.md` or equivalent instructions file).

Your Memco MCP endpoint is:

```
https://spark.memco.ai/mcp
```

Authentication is handled via OAuth. When your MCP client connects for the first time, it will redirect you to sign in and authorize the connection. Alternatively, you can authenticate using an API key generated from the [Memco dashboard](https://spark.memco.ai/).

**Claude Desktop** — add the following to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "memco-shared-memory": {
      "url": "https://spark.memco.ai/mcp"
    }
  }
}
```

**Cursor** — add to your MCP settings in `.cursor/mcp.json`:

```json
{
  "mcpServers": {
    "memco-shared-memory": {
      "url": "https://spark.memco.ai/mcp"
    }
  }
}
```

**Claude Code** — add from the command line:

```bash
claude mcp add memco-shared-memory --transport streamable-http https://spark.memco.ai/mcp
```

## Verify the connection

Once connected, your agent should have access to Memco's tools. Ask your agent to list the available domains:

> "What Memco domains do I have access to?"

A typical response includes `coding` for software development and `knowledge` for broader knowledge work.

## Search and contribute

Your agent can now search for existing knowledge:

> "Search Memco for best practices on error handling in this codebase"

And contribute new knowledge when it learns something useful:

> "Save this as a memory in Memco — the payments service requires idempotency keys on all POST requests"

The agent handles the tool calls automatically. No code changes or API integration are needed beyond the initial configuration.

## Next steps

- [Learning on the Job](/examples/learning-on-the-job) — a complete runnable example: an agent learning a business's policies from reviewer corrections, with a measured learning curve
- [MCP overview](/mcp/overview) — how the MCP connection works, including multi-domain support
- [MCP tools reference](/mcp/tools-reference) — the complete tool surface
- [How Memco works](/concepts/how-memco-works) — the memory lifecycle in detail
- [Knowledge domains](/concepts/knowledge-domains) — how domains shape what your agents learn