Locally invokes a Lambda function using AWS SAM CLI. Requirements: - AWS SAM CLI MUST be installed and configured in your environment - Docker must be installed and running in your environment. This command runs your Lambda function locally in a Docker container that simulates the AWS Lambda en...
High parameter count (13 properties)
Part of the AWS Serverless MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke sam_local_invoke to trigger processes or run actions in AWS Serverless MCP Server. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
sam_local_invoke can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
sam_local_invoke:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full AWS Serverless MCP Server policy for all 32 tools.
Agents calling execute-class tools like sam_local_invoke have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
sam_local_invoke is one of the high-risk operations in AWS Serverless MCP Server. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Locally invokes a Lambda function using AWS SAM CLI. Requirements: - AWS SAM CLI MUST be installed and configured in your environment - Docker must be installed and running in your environment. This command runs your Lambda function locally in a Docker container that simulates the AWS Lambda environment. Use this tool to test your Lambda functions before deploying them to AWS. It allows you to test the logic of your function faster. Testing locally first reduces the likelihood of identifying issues when testing in the cloud or during deployment, which can help you avoid unnecessary costs. Additionally, local testing makes debugging easier to do. Returns: Dict: Local invoke result and the execution logs. It is categorised as a Execute tool in the AWS Serverless MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for sam_local_invoke. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AWS Serverless MCP Server MCP server.
sam_local_invoke is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the sam_local_invoke rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for sam_local_invoke. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
sam_local_invoke is provided by the AWS Serverless MCP Server MCP server (awslabs.aws-serverless-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.