Levo’s MCP Discovery to end MCP Sprawl
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MCP is accelerating both:
AI integration and security risks
MCP did not arrive through a controlled enterprise rollout. It spread through developer workflows, internal prototypes, and quick utility installs that become permanent. With ecosystem growth accelerating, security teams need a live inventory to avoid discovering MCP only after it becomes business-critical.
Endpoint MCP servers often sit closest to valuable local context, including files, logs, tokens, cached credentials, and developer environments. When those servers are not enumerated, teams cannot define what exists, what it can reach, or what it can trigger. That blind spot turns AI “integration speed” into untracked execution risk.
In MCP ecosystems, teams pull servers because they work, then those servers quickly become embedded in everyday workflows. Without a clear approved vs unapproved view, adoption becomes accidental, not intentional. Policy stays on paper while real usage moves elsewhere.
An inventory is helpful, but a prioritized inventory is actionable. When risk posture is not ranked across the MCP footprint, teams chase noise while high-impact servers linger. That uncertainty makes every scale decision feel like a gamble.
MCP servers can introduce new outbound connections, new tool paths, and new access patterns that were never reviewed as an execution plane. When reach and behavior are not surfaced early, exposure becomes “normal” before controls exist. The first time leadership sees the risk is often during an escalation.
Enterprises do not want blanket shutdowns because the productivity upside is real. They want targeted containment for the few MCP servers, tools, or access patterns that cross the line. Selective controls keep MCP adoption moving while preventing sprawl from turning into an incident that pauses AI programs.
MCP Discovery that fuels MCP Security
Inventory and classify every MCP server
Levo continuously discovers MCP servers across developer laptops, prototypes, production environments and third-party services. It integrates with MDM and endpoint agents to build a living inventory that includes location, owner and context. Approved versus unapproved classification turns this map into an enforceable baseline, eliminating blind spots and shadow usage.
Turn discovery into governance and prioritization
Levo builds a single enterprise repository of MCP servers across both in-house deployments and third-party sources. Each server is enriched with ownership, environment context, and usage signals, then assigned a risk score that reflects real exposure. High-risk servers surface first for remediation and containment, while lower-risk servers remain visible and governable.
Surface endpoint exposures and enforce security controls
MCP servers can access local files, logs, tokens and cached credentials. Levo surfaces what each server can reach and highlights unsafe patterns before they become part of normal workflows. It then applies policies to restrict sensitive access, enforce encryption and authentication, and integrate with existing tooling, preventing data loss and lateral movement from endpoints.
Selectively block high‑risk behaviour without stopping innovation
When a server exhibits dangerous patterns, Levo can block those actions selectively while letting the rest of the workflow continue. This context‑aware containment keeps teams moving fast while isolating abuse, so security does not become a productivity tax.
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Operate at enterprise scale with minimal friction
MCP Discovery deploys via existing MDM and endpoint agents, requiring no proxies or rewrites. It operates continuously with low overhead, ensuring up‑to‑date coverage without constant tuning. Governance becomes part of the rollout rather than a separate, high‑effort project, so organisations can expand AI capabilities confidently.
Governed MCP adoption benefits every team
Reduce the daily burden of unknown execution paths created by fast-moving MCP adoption. A living MCP repository with risk posture enables faster triage, fewer emergency reviews, and fewer “pause the rollout” moments when new servers appear late.
Keep MCP-driven delivery velocity without triggering late-stage security rewrites and rollback cycles. When MCP servers are visible, classified, and prioritized early, productionization becomes a predictable path instead of a negotiation.
When MCP servers are tracked across in-house and third-party sources with clear posture and accountability, audit readiness improves and regional governance becomes practical without slowing adoption.
Know your MCP footprint. Keep AI velocity intact.
Frequently Asked Questions
Got questions? Go through the FAQs or get in touch with our team!
What is MCP, and why are enterprises adopting it so quickly?
MCP is a standard way for AI systems to connect to tools, data sources, and business workflows through a consistent interface. Enterprises adopt it because it reduces integration effort and makes it easier to add new capabilities without rebuilding connectors repeatedly. It also enables faster experimentation because teams can plug agents into real systems with less overhead. The tradeoff is that MCP can spread faster than governance. Levo’s MCP Discovery helps enterprises adopt MCP with the visibility and control needed to scale safely.
What is MCP Discovery, and what problem does it solve?
MCP Discovery is the capability to continuously identify which MCP servers exist and are being used across an organization. It solves the core problem that governance cannot be enforced on a footprint that is not known. Without discovery, security and IT teams cannot confidently separate sanctioned usage from shadow installs or prioritize where to focus first. Discovery turns MCP sprawl into an inventory that can be governed and secured. Levo’s MCP Discovery delivers continuous inventory, classification, and prioritization across endpoint and remote MCP environments.
Why do enterprises need to govern MCP adoption?
MCP becomes an execution layer for agents, not just a connectivity convenience. When adoption is decentralized, teams can unintentionally introduce unapproved servers into workflows that touch sensitive systems and data. That creates unknown exposure paths, unclear accountability, and inconsistent controls across teams and environments. Governance makes MCP adoption intentional by defining what is allowed, what is risky, and what must be contained. Levo’s MCP Discovery makes that governance possible by establishing a complete and current MCP baseline.
What is “shadow MCP,” and why is it risky?
Shadow MCP is MCP usage that exists outside approved registries and formal review, often installed locally or adopted informally by teams under delivery pressure. It is risky because it creates unknown tool execution surfaces and exposure paths that security cannot assess or constrain. Shadow MCP also makes incident response harder because ownership and inventory are unclear. Over time, “temporary” installs become embedded in business workflows. Levo’s MCP Discovery surfaces shadow MCP and differentiates approved vs unapproved usage so enforcement can be real.
How do enterprises find MCP servers running on laptops and endpoints?
Endpoint MCP often requires visibility through enterprise fleet controls rather than manual reporting. Without operational alignment, discovery becomes incomplete and quickly outdated. The practical approach is to integrate with existing endpoint management patterns so coverage is consistent across the fleet. This avoids reliance on tribal knowledge and one-time audits. Levo’s MCP Discovery is designed to fit into enterprise endpoint operations so endpoint MCP usage becomes visible and governable.
How do enterprises discover MCP servers in staging, production, and remote environments?
Remote MCP servers often sit in environments where teams iterate rapidly, which can create drift between what is deployed and what is documented. Discovery should enumerate servers continuously across environments so governance stays current as MCP evolves. Without that, organizations end up governing what they think exists instead of what actually exists. A live enterprise inventory makes enforcement and prioritization possible. Levo’s MCP Discovery covers both local and remote MCP servers to establish a single, current footprint.
What does “approved vs unapproved MCP servers” mean in practice?
It means MCP servers are classified based on whether they meet enterprise standards for security, ownership, and acceptable behavior. This classification is what converts a raw inventory into an enforceable footprint. Without it, MCP adoption becomes accidental because teams treat “installed” as “safe.” With it, leadership can make clear decisions about what belongs and what must be contained. Levo’s MCP Discovery performs approved vs unapproved classification so policy can be applied consistently.
How does MCP risk scoring work, and why does it matter?
Risk scoring ranks MCP servers based on their behavior, reach, environment placement, and how widely they are relied on. This matters because an unprioritized inventory creates analysis paralysis and slows remediation. A ranked view turns governance into action by showing what needs attention first. It also reduces friction because security teams can focus on high-impact risks rather than reviewing everything equally. Levo’s MCP Discovery assigns risk posture across the MCP footprint so decisions become faster and more deliberate.
What are the biggest MCP security risks enterprises should protect against?
The biggest risks come from unknown execution surfaces, unapproved servers entering workflows, and unclear exposure paths to sensitive systems or local context. MCP can also expand supply chain risk when teams pull third-party servers without standard review. The impact is not only technical. Incidents and uncertainty slow AI rollouts because leaders cannot prove control. Levo’s MCP Discovery reduces these risks by making MCP usage visible, classifiable, and prioritizable.
How do you secure MCP servers after discovery?
Securing MCP starts once the MCP footprint is visible. When it is clear which servers exist, where they run, and who uses them, controls can be applied to the real exposure paths instead of broad, disruptive restrictions. That typically includes defining what servers are approved, limiting what tools can be invoked, and containing risky servers before they become dependencies. The goal is to keep MCP adoption moving while reducing the chance of a single weak server creating a larger incident. Levo’s MCP Discovery provides the continuously updated inventory and context needed to apply MCP security controls with precision.
When should an MCP server be blocked or disabled?
Blocking makes sense when an MCP server crosses a defined risk threshold, such as running in an untrusted location, showing unusual usage patterns, or enabling access paths that violate policy. Most enterprises avoid blanket shutdowns because MCP often underpins real productivity gains across teams. The practical approach is targeted containment that isolates the specific risky server, tool path, or access pattern without breaking everything else. This prevents small exposures from escalating into incidents that force a wider pause on AI adoption. Levo’s MCP Discovery supports selective blocking by surfacing high-risk servers early and enabling action where policy requires it.
What is the first step to MCP security for an enterprise?
The first step is establishing a reliable baseline of what MCP exists in the environment. Without that, governance is theoretical because policies cannot be applied consistently to unknown servers, endpoint installs, or third-party instances. A strong baseline stays current as teams add servers, change tools, and shift environments, otherwise oversight falls behind again. Once that living view exists, security teams can prioritize risk, standardize approved usage, and apply enforcement where posture demands. Levo’s MCP Discovery is built to operationalize this first step at enterprise scale by continuously maintaining an inventory of both in-house and third-party MCP servers with ownership and risk context.
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