Governed Stack
MPLP does not replace agent frameworks, MCP, or runtimes. It governs them — by enforcing lifecycle contracts (intent, authorization, audit) across the stack.
Core Principle
Governed Objects, Not Competitors
MPLP is a protocol-layer governance shell: it defines what systems must prove (intent → authorization → evidence), not how they should be implemented.
Modern agent stacks are assembled from multiple layers: orchestration frameworks, tool protocols, runtimes, and cloud platforms. The failure mode is not lack of features — it is lack of governable evidence.
MPLP makes the stack governable by enforcing lifecycle contracts: Plan (explicit intent), Confirm (policy & authorization), Trace (auditable evidence).
What MPLP governs
lifecycle semantics, approvals, evidence, replayability
What others provide
orchestration, tools, execution, platform integrations
Outcome
vendor-neutral governance across heterogeneous stacks
Architecture
Compliance as a Kernel Responsibility
In MPLP, compliance is not implemented as an external plugin or optional middleware. It is a kernel-level responsibility enforced through protocol-defined lifecycle duties.
Kernel-Level Enforcement
Compliance checks are baked into the agent's lifecycle loop. An agent cannot transition from Plan to Act without passing kernel-level authorization gates.
- ✓11 Kernel Duties define mandatory checks
- ✓Authorization Gates block unauthorized actions
- ✓Evidence Chain is immutable and continuous
Plugin-Level (Traditional)
In traditional architectures, compliance is often an “afterthought” wrapper or a sidecar proxy that can be bypassed or disabled.
- ✗Compliance logic external to agent state
- ✗Can be bypassed by direct API calls
- ✗Audit trails are fragmented
Usage Boundary: This section clarifies architectural responsibility. It does not assert regulatory compliance for any specific implementation without independent audit.
Decision Guide
How teams actually choose an agent stack
Start with constraints (security, cloud lock-in, ops model), then pick execution components. MPLP is the governance shell that stays stable across those choices.
Step 1 — Identify hard constraints
- • Regulated environment / audit required?
- • Multi-cloud or hybrid deployment?
- • Need strict RBAC / approval gates?
- • Need reproducibility & incident reconstruction?
If any answer is “yes”, you need a governance shell. That is where MPLP sits.
Step 2 — Select execution components
- • Orchestration: graphs / crews / planners
- • Tool protocol: MCP servers and connectors
- • Runtime: action execution & sandboxing
- • Platform: cloud-native or self-hosted
These can change over time. MPLP keeps governance stable while components evolve.
Fast prototyping
Pick a framework → wrap with MPLP when going to production
Enterprise governance
Start with MPLP → choose any orchestrator/runtime underneath
Tool ecosystem
Use MCP for tools → govern access & evidence via MPLP
Avoid lock-in
Keep governance vendor-neutral → swap clouds/models safely
Architecture View
Protocol above, execution below
MPLP sits above frameworks and tool protocols as a lifecycle governance layer. It does not compete with them — it makes them governable.
Reference Matrix
Governed objects and governance gaps
What each system does well, what it typically does not guarantee, and what MPLP adds as a governance shell.
| System | Primary job | Typical governance gap | What MPLP governs |
|---|---|---|---|
| MCP | Tool/resource access standard | Access control and audit posture varies by deployment and server implementation | Policy gates (Confirm), evidence trails (Trace), scoped intent (Plan) |
| LangGraph / orchestration graphs | Workflow execution & state transitions | Great execution control, but “audit-grade intent + approvals” is not guaranteed by default | Intent capture, approval gates, standardized trace semantics across frameworks |
| Agent Frameworks / Platforms | End-to-end platform integration | Strong platform guarantees, but portability and vendor-neutral governance may be constrained | Vendor-neutral governance contracts; multi-cloud lifecycle portability |
| Execution runtimes (operators) | Action execution & side-effects | Side-effects are where incidents happen — without formal gating, audit is post-hoc | Mandatory confirmation before high-risk actions; replayable evidence chains |
Security Reality Check
Why governance becomes urgent as ecosystems scale
When tool ecosystems expand rapidly, security posture becomes uneven. Enterprises need a governance shell that enforces identity, authorization, and evidence — consistently.
The pattern
Tool servers and connectors often emerge faster than security norms. The result is not “MCP is unsafe” — the result is that security becomes optional in practice.
What MPLP changes
MPLP forces high-risk operations through Confirm gates, binds actions to explicit Plan, and records Trace evidence — regardless of which tool protocol or framework you use.
Recipes
Composable integrations that enterprises actually deploy
Start with the components you already use. Add MPLP as the governance shell without replatforming.
Recipe 1 — MPLP + MCP
Use MCP for tool/data access. Wrap tool calls with MPLP Plan/Confirm/Trace so every access is scoped, authorized, and auditable.
Best for
tool ecosystems, connector-heavy stacks
Recipe 2 — MPLP + Orchestrator
Keep your orchestrator (graphs/crews). MPLP standardizes lifecycle events and evidence semantics across runs, enabling audit, replay, and governance at scale.
Best for
complex workflows, multi-step automation
Recipe 3 — MPLP for multi-cloud
When platforms differ, governance must not. MPLP provides vendor-neutral lifecycle contracts so stacks can move across clouds without rewriting governance logic.
Best for
hybrid environments, portability mandates
Recommended next reads: Evidence Chain · NIST AI RMF Alignment