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72 lines
2.7 KiB
Markdown
72 lines
2.7 KiB
Markdown
# Model Context Protocols (MCP) and adding AI tools
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> [!NOTE]
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>
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> This functionality is in beta and is evolving rapidly.
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>
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> When using any AI tool for development, exercise a level of caution appropriate to your use case and environment.
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> Always review AI-generated content before using it in critical systems.
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>
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> Join our [Discord channel](https://discord.gg/coder) or
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> [contact us](https://coder.com/contact) to get help or share feedback.
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## Overview
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Coder templates should be pre-equipped with the tools and dependencies needed
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for development. With AI Agents, this is no exception.
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## Prerequisites
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- A Coder deployment with v2.21 or later
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- A [template configured for AI agents](./create-template.md)
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## Best Practices
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- Use the most capable ML models you have access to in order to evaluate Agent
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performance.
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- Set a system prompt with the `AI_SYSTEM_PROMPT` environment in your template
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- Within your repositories, write a `.cursorrules`, `CLAUDE.md` or similar file
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to guide the agent's behavior.
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- To read issue descriptions or pull request comments, install the proper CLI
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(e.g. `gh`) in your image/template.
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- Ensure your [template](./create-template.md) is truly pre-configured for
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development without manual intervention (e.g. repos are cloned, dependencies
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are built, secrets are added/mocked, etc.).
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> Note: [External authentication](../admin/external-auth.md) can be helpful
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> to authenticate with third-party services such as GitHub or JFrog.
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- Give your agent the proper tools via MCP to interact with your codebase and
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related services.
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- Read our recommendations on [securing agents](./securing.md) to avoid
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surprises.
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## Adding Tools via MCP
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Model Context Protocol (MCP) is an emerging standard for adding tools to your
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agents.
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Follow the documentation for your [agent](./agents.md) to learn how to configure
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MCP servers. See
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[modelcontextprotocol/servers](https://github.com/modelcontextprotocol/servers)
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to browse open source MCP servers.
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### Our Favorite MCP Servers
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In internal testing, we have seen significant improvements in agent performance
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when these tools are added via MCP.
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- [Playwright](https://github.com/microsoft/playwright-mcp): Instruct your agent
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to open a browser, and check its work by viewing output and taking
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screenshots.
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- [desktop-commander](https://github.com/wonderwhy-er/DesktopCommanderMCP):
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Instruct your agent to run long-running tasks (e.g. `npm run dev`) in the
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background instead of blocking the main thread.
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## Next Steps
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- [Supervise Agents in the UI](./coder-dashboard.md)
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- [Supervise Agents in the IDE](./ide-integration.md)
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- [Supervise Agents Programmatically](./headless.md)
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- [Securing Agents](./securing.md)
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