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Embedder can connect to hundreds of external tools and data sources through the Model Context Protocol (MCP), an open source standard for AI-tool integrations. MCP servers give Embedder access to your tools, databases, and APIs.

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What you can do with MCP

With MCP servers connected, you can ask Embedder to:
  • Implement features from issue trackers: “Add the feature described in Linear issue ENG-4521 and create a PR on GitHub.”
  • Analyze monitoring data: “Check Sentry for errors related to the serial monitor and summarize the most common crashes.”
  • Search the web: “Use Firecrawl to find the latest ESP-IDF release notes and summarize what changed in the Wi-Fi driver.”
  • Track issues across tools: “Find all open Jira issues tagged ‘firmware’ in Atlassian and cross-reference with related Sentry errors.”

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Configure MCP servers

Add and manage MCP servers with the /mcp command.
1

Run /mcp

Use the /mcp command to see the preconfigured MCPs Embedder has, or to add your own.
2

Add a server

MCP servers panel showing installed servers and marketplace options

The /mcp command shows your installed servers and the marketplace

Either select an MCP server from the marketplace, or press a to add your own.
Add MCP Server form with fields for name, type, and command

Add a custom MCP server by providing a name, transport type, and command

3

Verify the connection

Once configured, Embedder automatically connects to the MCP server. You can verify the connection by asking Embedder to list available tools.
Only use MCP servers from trusted sources.

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Supported transports

Embedder supports the following MCP transport types:
  • stdio — Communicates with the server over standard input/output. This is the most common transport for local servers.
  • SSE — Connects to a remote server over Server-Sent Events. Use this for hosted or shared MCP servers.
  • HTTP — Connects to a remote server over HTTP. Use this for stateless or REST-based MCP servers.
Last modified on March 5, 2026