MCP2Lambda

What it is

A bridge between an MCP client and AWS Lambda. The client holds credentials that can only invoke functions; each function then reaches whatever it needs — other AWS services, a VPC, the public internet — under its own execution role. That split is the design: the model can call the function but cannot touch what the function touches.

What you get

• Autodiscovery of the Lambda functions in your account that match a prefix or an allowed list, passing their names and descriptions to the model
• Invocation of those functions by name with parameters
• Pre-Discovery Mode, on by default, which registers each function as its own named tool
• Generic Mode as the alternative — two tools, list_lambda_functions and invoke_lambda_function — selected with PRE_DISCOVERY=false or the --no-pre-discovery flag
• A default name filter: only functions starting with mcp2lambda- are offered to the model
• Three sample functions in the repo, deployable with sam build and sam deploy, including one that runs arbitrary Python inside the Lambda sandbox

Requirements

Python 3.12 or higher, an AWS account with credentials configured (aws configure), and the functions you want to expose. The package is mcp2lambda, started with uv run main.py. One thing carries more weight than any setting: the model reads each function's own Lambda description to decide when to call it, so that description has to say what the function does and which parameters it takes.

Setup effort

Build from source — git clone https://github.com/danilop/mcp2lambda.git

Tools you get

2 tools named in the project's documentation. These two are the Generic Mode tools, which the Claude Desktop block below selects with PRE_DISCOVERY=false. In the default Pre-Discovery Mode the server registers each matching Lambda function as its own tool instead, so the count depends on your account.

Requires

• Python 3.12 or later
• uv on PATH

Where it runs

The documented client runs the server on your machine.