Proposal: Add EMCL support to secure LangChain ToolCalls using AES-GCM + HMAC + JWT

[Balchandar]

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Feature request

Add EMCL support for secure LangChain ToolCalls using AES-GCM + HMAC + JWT

Motivation

LangChain’s ToolCall interface is currently JSON-based and does not provide:

Encryption of parameters or results

Verification of sender identity (agent)

Replay protection or request integrity

In real-world deployments — especially in healthcare, finance, or autonomous agents — this leaves agent–tool communication vulnerable to interception, spoofing, or tampering.

A secure protocol layer is essential for enterprise-grade AI systems.

Proposal (If applicable)

I propose integration (or optional support) for EMCL (Encrypted Model Context Layer):

A secure JSON-RPC wrapper built on MCP (Model Context Protocol)

Wraps each ToolCall request with:

AES-256-GCM encryption of tool parameters/results

HMAC-SHA256 signature over the payload

JWT identity propagation for agent authentication

Nonce + timestamp–based replay protection