Future-Proof Your AI Stack with Open Agentic Protocols
Future-proof AI runs on open rails: MCP for data & tools (with an MCP Proxy Bridge for legacy apps), A2A for agent-to-agent delegation, ACP for governance & routing, and A2H/H2A for human-in-the-loop decisions.
By Dickey Singh

This article is the second in a two-part series. The first article can be found here: Where are you placing your CX chips? Generalist Super Agent or Multiple Specialized Agents?

Executive Summary

The smartest play is neither an all-knowing Super-Agent nor a swarm of siloed specialist agents—it’s a hybrid: a powerful generalist agent (with several agent personas) that steers the conversation, flanked by specialist agents that fire off API/tool calls, search the web, tap knowledge bases, and trigger tools on demand.

This only works if agents can talk to each other, to your data and tools, and to humans using open, reusable protocols—so you wire a connector once and reuse it everywhere instead of rebuilding brittle point-to-points.

This guide shows revenue and CX leaders how to sidestep agent-sprawl and integration chaos—and why Cast’s open-protocol fabric puts you two steps ahead of vendor lock-in.

Collaborating Agents, Data, and People

Your agents must interoperate with:

  • Other agents (delegate, hand off, share artifacts)
  • Data & tools (query and act under policy)
  • Humans (approvals/escalations)
Your AI agents must talk to each other—and your data and people—without chaos.

Why P&L leaders care

Open protocols give agents a shared language. Wire it once, reuse it everywhere—no more brittle one-off connectors.

  • Consistency: one grammar → fewer bespoke builds and fire-drills
  • Swap-ready: change vendors without rewiring
  • Governed & secure: standard auth, policy, and audit calm CFO/CISO nerves
  • Future-proof: upgrades, not rewrites
  • Better ROI: less integration debt, faster time-to-value
  • Process-safe: Minimize the Change-management tax.

The Protocols

Agents need to talk to data, each other, and humans.

Agent ↔︎ Data: MCP, MCP Proxy Bridge
Agent ↔︎ Agent: ACP, A2A
Agent ↔︎ Human: A2H, H2A

Below are five key protocols that form an end-to-end fabric for data access, inter-agent hand-offs, and human collaboration.

Agents connecting to Data, Legacy Data, Agents, Agents (intra- or cross-org), and Humans

1. Model Context Protocol (MCP) Agent ↔︎ Data

MCP was proposed by Anthropic and has wide acceptance.

MCP lets agents discover tools and call them to query or act on external systems (files, DBs, SaaS APIs, code execution). It’s bidirectional under policy—not read-only.

2. Model Context Protocol Proxy Bridge (MPB) Agent ↔︎ Legacy Data

Think of MPB as a thin wrapper that lets REST/webhook apps—HubSpot, Zendesk, you name it— present an MCP-compatible façade and an optional A2A handoff shim until a native agent exists.

It solves legacy lock-in—use it when you must integrate a non-compliant system today and don’t want to rebuild tomorrow.

Why execs care

  • No vendor lock-in—ship integrations today, swap in native agents tomorrow
  • Future-proof—your workflows never rewrite; just point to the new agent ID

Example: A legacy CRM exposes a renewal endpoint; MPB masks its quirks so every agent treats it like a modern MCP source.

3. Agent Communication Protocol (ACP) Agent ↔︎ Agent

IBM

ACP is an open agent↔agent standard to reduce fragmentation and enable collaboration across stacks;

IBM contributed BeeAI—powered by the open Agent Communication Protocol (ACP)—to the Linux Foundation, establishing open, community governance for ACP and its reference implementation.

Important naming note on “ACP.” There are two unrelated ACPs in the market:

  • Agent Communication Protocol (IBM) — agent↔agent messaging/interoperability.  
  • Agentic Commerce Protocol (Stripe & OpenAI) — an e-commerce spec for agent-initiated checkout flows (can be implemented as REST or MCP). Different purpose entirely.

4. Agent2Agent Protocol (A2A) Agent ↔︎ Agent

Google

A2A defines how agents discover capabilities, delegate tasks, exchange artifacts, and manage lifecycles across frameworks and vendors; transport-agnostic, usable within or across org boundaries.

A2A introduces Agent Cards for capability discovery and standardizes task lifecycle and artifact exchange, with transport over HTTP/SSE/JSON-RPC.

5a. Agent-to-Human Transfer (A2H) Agent ↔︎ Human

Cast.app

A smart escalation layer: agents decide when to loop in a human, picking the right person, channel, and context.

It solves moments where empathy or judgment boosts revenue or mitigates risk—use A2H when a human touch can save, upsell, or de-risk.

Example: Usage spikes trigger an A2H alert to the VP via email (complete with benchmarks); after approval, the agent resumes automated upsell steps.

5b. Human-to-Agent Transfer (H2A) Human ↔︎ Agent

cast.app

The mirror image of A2H—a secure command interface so people can instruct agents to act on their behalf.

It solves high-trust tasks that are faster or safer for an agent to execute. Invoke H2A whenever a human needs precise, error-free action.

Example: A finance manager tells the Payments Agent to issue a refund via Stripe, or a support rep asks the Security Agent to trigger 2-factor authentication for a user.

With these six protocols in place, your hybrid agent ecosystem—generalist strategists plus deep specialists—can share data, delegate work, and involve humans only when it truly counts.

BTW, if you are running cast.app agents, all the complexity solved for you.

Final Takeaway

Rule of thumb: A2A handles “what/why/results,” ACP standardizes “who/where/allowed,” MCP is “how to access systems.”

Cast.app weaves six pieces of connective tissue—MCP, MCP Proxy Bridge, ACP, A2A, A2H, and H2A—into one seamless fabric so your AI CSMs, Feedback Agents, and Support Agents operate like a single, revenue-focused brain.

What this means for leaders

  • Immediate impact: Stand up AI CSM autopilots that handle routine work and deliver ROI.
  • Zero re-plumbing: MPB lets you integrate any legacy SaaS today and swap in native agents tomorrow without touching workflows.
  • Future-proof growth: Open standards ensure every new data source, partner agent, or human escalation drops in—no added headcount, no hidden debt.

Scale revenue, not teams—Cast.app handles the wiring.

Select References

  1. Anthropic — Model Context Protocol launch, Nov 2024
  2. MCP Specification
  3. IBM Think Blog — “What is ACP?”, May 2025
  4. Linux Foundation Press Release (Apr 29, 2025): AI workflows get new open-source tools (notes BeeAI powered by ACP, contributed to LF).  
  5. IBM Research Blog (May 28, 2025): An open-source protocol for AI agents to interact (states BeeAI + ACP contributed to the Linux Foundation)
  6. Stripe & Open AI Agentic Commerce Protocol
  7. Google Developers Blog — Agent-to-Agent protocol
  8. Cast.app Blog — “Copilots vs Autopilots,” Jun 2024
    https://cast.app/ai-copilots-versus-ai-autopilots
  9. ReAct (Reason + Act) – a prompting framework where a single language model alternates between “thinking” (Reason) and executing tool calls or API actions (Act) to solve complex tasks step-by-step. Source: Yao, Shunyu et al., “ReAct: Synergizing Reasoning and Acting in Language Models,” arXiv preprint arXiv:2210.03629 (2023).
  10. Open AI Operator Super Agent https://openai.com/index/introducing-operator/?utm_source=cast.app
  11. Operator + Vox
  12. Multi-Agent systems

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