This MCP server acts as a **bridge** between MCP clients and AWS Lambda functions, allowing generative AI models to access and run Lambda functions
MCP2Lambda MCP server exists for a simple reason — assistants are far more useful when they can act on MCP2Lambda directly instead of describing what you should do. This MCP server acts as a bridge between MCP clients and AWS Lambda functions, allowing generative AI models to access and run Lambda functions as tools. This is useful, for example, to access private resources such as internal.
MCP2Lambda enables LLMs to interact with AWS Lambda functions as tools, extending their capabilities beyond text generation. This allows models to:
The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Once MCP2Lambda is connected, these are the calls the assistant has available:
CustomerIdFromEmail — Retrieves a customer ID based on an email address. This function takes an email parameter and returns the associated customer ID, demonstrating howCustomerInfoFromId — Retrieves detailed customer information based on a customer ID. This function returns customer details like name, email, and status, showing howRunPythonCode — Executes arbitrary Python code within a Lambda sandbox environment. This powerful function allows Claude to write and run Python code to performPrerequisites — The Prerequisites tool exposed by this serverConfiguration — The client is configured to use Anthropic's Claude 3.7 Sonnet by default, but you can modify the model_id in main.py to use other Bedrock models:Usage — 1. Start the MCP2Lambda server in one terminal: cd mcp2lambda uv run main.pyYou will need one environment variable: PRE_DISCOVERY. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the team communication group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MCP2Lambda's toolset — CustomerIdFromEmail, CustomerInfoFromId, RunPythonCode and 3 more — is a fair guide to whether it matches your workflow. It is maintained by danilop; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against MCP2Lambda's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| CustomerIdFromEmail | Retrieves a customer ID based on an email address. This function takes an email parameter and returns the associated customer ID, demonstrating how to build simple lookup tools. The function is hard coded to reply to the |
| CustomerInfoFromId | Retrieves detailed customer information based on a customer ID. This function returns customer details like name, email, and status, showing how Lambda can provide context-specific data. The function is hard coded to rep |
| RunPythonCode | Executes arbitrary Python code within a Lambda sandbox environment. This powerful function allows Claude to write and run Python code to perform calculations, data processing, or other operations not built into the model |
| Prerequisites | The Prerequisites tool exposed by this server. |
| Configuration | The client is configured to use Anthropic's Claude 3.7 Sonnet by default, but you can modify the model_id in main.py to use other Bedrock models: |
| Usage | 1. Start the MCP2Lambda server in one terminal: cd mcp2lambda uv run main.py |
{
"mcpServers": {
"mcp2lambda": {
"command": "npx",
"args": ["-y", "@smithery/cli"],
"env": {
"PRE_DISCOVERY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| PRE_DISCOVERY | Configuration value read at startup. | Optional |
Your assistant inside the workspace — read channels, search history, post messages and tame the noise.
Inbox intelligence — search, read, draft and send Gmail through your assistant with OAuth auto-setup.
Read and write Jira, Confluence, Bitbucket, JSM and Compass from your AI client — with your own permissions.
Read and send Telegram messages through your assistant — chats, channels and history via the client API.
Enables Discord bot integration with Model Context Protocol (MCP) compatible applications like Claude Desktop.
Exposes REST APIs defined by OpenAPI specifications as Model Context Protocol (MCP) tools, facilitating seamless integration into MCP-based workflows.