MCP2Lambda

Run anyAWS Lambdafunction as a Large Language Model (LLM)toolwithout code changes usingAnthropic'sModel Context Protocol (MCP).

graph LR A[Model] <--> B[MCP Client] B <--> C["MCP2Lambda<br>(MCP Server)"] C <--> D[Lambda Function] D <--> E[Other AWS Services] D <--> F[Internet] D <--> G[VPC] style A fill:#f9f,stroke:#333,stroke-width:2px style B fill:#bbf,stroke:#333,stroke-width:2px style C fill:#bfb,stroke:#333,stroke-width:4px style D fill:#fbb,stroke:#333,stroke-width:2px style E fill:#fbf,stroke:#333,stroke-width:2px style F fill:#dff,stroke:#333,stroke-width:2px style G fill:#ffd,stroke:#333,stroke-width:2px

This MCP server acts as abridgebetween 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 applications and databases without the need to provide public network access. This approach allows the model to use other AWS services, private networks, and the public internet.

From asecurityperspective, this approach implements segregation of duties by allowing the model to invoke the Lambda functions but not to access the other AWS services directly. The client only needs AWS credentials to invoke the Lambda functions. The Lambda functions can then interact with other AWS services (using the function role) and access public or private networks.

The MCP server gives access to two tools:
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The first tool canautodiscoverall Lambda functions in your account that match a prefix or an allowed list of names. This tool shares the names of the functions and their descriptions with the model.

The second tool allows toinvokethose Lambda functions by name passing the required parameters.

No code changes are required. You should change these configurations to improve results:

The gateway supports two different strategies for handling Lambda functions:
-

Pre-Discovery Mode(default: enabled): Registers each Lambda function as an individual tool at startup. This provides a more intuitive interface where each function appears as its own named tool.

Generic Mode: Uses two generic tools (list_lambda_functionsandinvoke_lambda_function) to interact with Lambda functions.

- Environment variable:PRE_DISCOVERY=true|false
- CLI flag:--no-pre-discovery(disables pre-discovery mode)

# Disable pre-discovery mode export PRE_DISCOVERY=false python main.py # Or using CLI flag to disable pre-discovery python main.py --no-pre-discovery

-

To provide the MCP client with the knowledge to use a Lambda function, thedescription of the Lambda functionshould indicate what the function does and which parameters it uses. See the sample functions for a quick demo and more details.

To help the model use the tools available via AWS Lambda, you can add something like this to yoursystem prompt:

Use the AWS Lambda tools to improve your answers.

MCP2Lambda enables LLMs to interact with AWS Lambda functions as tools, extending their capabilities beyond text generation. This allows models to:

- Access real-time and private data, including data sources in your VPCs
- Execute custom code using a Lambda function as sandbox environment
- Interact with external services and APIs using Lambda functions internet access (and bandwidth)
- Perform specialized calculations or data processing

The server uses the MCP protocol, which standardizes the way AI models can access external tools.

By default, only functions whose name starts withmcp2lambda-will be available to the model.

- Python 3.12 or higher
- AWS account with configured credentials
- AWS Lambda functions (sample functions provided in the repo)
- An application usingAmazon Bedrockwith theConverse API
- An MCP-compatible client likeClaude Desktop

To install MCP2Lambda for Claude Desktop automatically viaSmithery:

npx -y @smithery/cli install @danilop/MCP2Lambda --client claude

git clone https://github.com/yourusername/mcp2lambda.git cd mcp2lambda

Configure AWS credentials. For example, using theAWS CLI:

Install the AWS SAM CLI:https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/install-sam-cli.html

cd sample_functions sam build sam deploy

Seehttps://github.com/mikegc-aws/amazon-bedrock-mcpfor more information.

# Examples of supported models: model_id = "us.anthropic.claude-3-7-sonnet-20250219-v1:0" #model_id = "us.amazon.nova-pro-v1:0"

{ "mcpServers": { "mcp2lambda": { "command": "uv", "args": [ "--directory", "<full path to the mcp2lambda directory>", "run", "main.py" ] } } }

To help the model use tools via AWS Lambda, in your settings profile, you can add to your personal preferences a sentence like:

Use the AWS Lambda tools to improve your answers.

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