Key Takeaways:
- Building an MCP gateway seems ‘cheap’ up-front but upkeep costs compound annually in engineering time required for support and management.
- Buy an MCP gateway when multiple teams share infrastructure and compliance requires audit trails.
- The bigger strategic question is whether one platform can govern MCP, LLM, and API traffic together instead of three separate control planes.
An MCP gateway prototype takes weeks to stand up as an internal pilot project, but governing it in production takes years. Building an MCP Gateway means investing regular engineering hours for upkeep.
This guide compares the real costs, compliance requirements, and governance depth of building your own MCP gateway versus buying one, and ends with a decision scorecard you can use.
What “build vs. buy” means for an MCP gateway
Building an MCP gateway means standing up your own aggregation layer by writing a service that authenticates users, routes requests to MCP servers, and logs what happened.
Buying an MCP gateway means adopting a vendor’s gateway that already does this work as either a self-hosted or managed service.
MCP itself is an open standard, just like API. What you’re really deciding is who owns the governance layer on top: identity, permissions, and audit trails. Most build-vs-buy advice gets this wrong.
What is an MCP gateway?
The Model Context Protocol (MCP) is the open standard, introduced by Anthropic in late 2024 that allows AI agents to call external tools through a common interface.
An MCP gateway is the relay between your agents and every MCP server they call. The gateway enforces your security policies: authentication, access control, and audit logging. MCPX is Lunar.dev’s MCP gateway, one of the first and best-known gateways in the category.
Build vs. buy at a glance
| Criteria | Build | Buy |
| Adoption scale | Single team, one cluster, under 5 MCP servers | Multi-team, multi-region, 10+ MCP servers |
| Ongoing maintenance | Engineering time spent monthly on protocol updates, credential rotation, and agent debugging | Vendor ships protocol updates as versioned releases |
| Time to production governance | Weeks for prototype, months to close compliance gaps | Days to weeks |
| Writing and hosting MCP servers | Hand-roll and self-host each server, own the validation | Hosted MCP servers plus a governed internal registry |
| MCP server security checks | Manual review that does not scale | MCP risk assessment and sandboxing, tool parameter pinning, shadow MCP detection |
| Agent identity management | Shared service accounts or custom code per agent | Per-employee identity binding via Agent Inventory (agent environment tracking) |
| Auth coverage | OAuth, static authentication, and IdP integrations built separately | OAuth, static OAuth, IdP integrations, in-client authentication, and RBAC built in |
| Audit trail | Bolted on per server, if at all | Audit trails on every tool call, plus anomaly detection |
| Access control | Custom ACL code your team owns | Role-based Profiles with Groups synced from your IdP, plus agent/user isolation and quarantine |
| Compliance readiness | SOC 2 evidence must be built | SOC 2 evidence provided |
| サポート | Your engineers on-call | Enterprise support and TAM |
ROI calculation: build vs. buy MCP gateway
The pattern is familiar: one AI tool gets rolled out and governed carefully, then more follow. Without a process for policy enforcement, soon agents are reaching into Jira, GitHub, and internal databases through connections nobody approved.
As connections grow without governance, three sources of internal cost start to add up:
Ongoing maintenance. MCP is still a moving protocol, and every server your agents call requires credentials and credential rotation. Rotating credentials across thousands of instances means tracking down every place a secret was used. At scale, this becomes a fire drill with no guaranteed end state.
Most teams don’t keep up: Astrix Security’s 2025 analysis of 5,200+ open-source MCP servers found 53% rely on static API keys or personal access tokens that are rarely rotated, with 79% of those keys passed as plain environment variables, exactly the gap OWASP’s MCP Top 10 names as its first risk category.
Protocol drift. As MCP matures, these should become uncommon. But they’re not hypothetical: MCP’s lead maintainers themselves shipped a release with the caveat “this release contains breaking changes, we don’t intend for that to be the norm,” and the specification versions each revision by the date of its last backward-incompatible change.
A breaking MCP spec change means internal triage across every connected server, patching client and server implementations, and re-testing agent workflows against the new behavior.
No SLA and no vendor coverage. A homegrown gateway has no support commitment. When an agent breaks before a demo, there’s no one to call but your own team.
Calculating Lifetime Build Cost
While the initial build investment can take a handful of sprints, there will always be a maintenance workload to keep an internally built product modern and functional.
Standing up an MCP gateway in-house could use $16,000 to $32,000 in hourly resources up front with 4 to 8 weeks of a senior engineer’s time at a $200k salary rate, plus $13,000 to $21,000 a year afterward to keep it running. This calculation needs to extend to the rest of the support structure the tool touches – internal documentation, training and adoption, integration, and analytics.
When building your own MCP gateway is the right call
Build if your footprint is genuinely small and compliance exposure is low.
Signs you’re a build candidate
- Fewer than five MCP servers, one team, one cluster.
- A static toolset, no plans to add teams or regions.
- No SOC 2, HIPAA, or ISO 27001 audit demanding centralized logs.
- Engineering willing to own credential rotation and auth code, permanently.
When buying an MCP gateway wins
Buy once more than one team needs shared infrastructure, or compliance starts asking questions your setup can’t answer.
Signs you’re a buy candidate
- More than five MCP servers, with multiple teams wanting to use them.
- Expanding toolsets and a tool catalog that includes vendor-created and self-hosted MCP servers.
- Your legal or regulatory environment requires an audit trail for agent activity.
How MCP Gateway increases AI adoption
Employees will default to personal AI accounts when company tools feel harder to use than the free alternatives. IDC’s research on EMEA found only 23% of employees use the AI tools their company provides, and more than half rely on personal accounts instead. This poses significant security risks, mainly credential exposure from poorly-configured MCP servers.
MCP Gateway addresses this at the access layer. Employees and agents authenticate through the existing IdP, so no new credentials get created. When a token expires, MCP Gateway exposes re-authentication as a tool the agent invokes, so non-technical users stay in their client instead of running a separate auth flow. Dynamic tool discovery surfaces newly approved servers as soon as they clear the catalog, and users see only the tools their role needs through role-based Profiles synced from the IdP.
Security still owns credential management, audits, and approvals while providing users with a list of tools they are authorized to access, instead of a wall of options they can’t use.
See how this plays out in enabling AI adoption beyond engineering.
Build vs. buy checklist
Score each item 0 to 2 for your situation. A higher total means buying is the safer path.
| Question | 0 | 1 | 2 |
| MCP servers you need in production | Under 5 | 5 to 10 | 10 or more |
| Teams using the gateway | One | Two to three | Four or more |
| Compliance requirements | None yet | Internal audit only | SOC 2, HIPAA, or ISO 27001 in scope |
| IdP breadth needed | None (static tokens acceptable) | One IdP, one integration | Multiple IdPs with per-employee identity |
| Non-technical users | None (Engineering only) | Some non-engineering usage | Non-engineering as primary users |
| Plan to add an LLM gateway or API gateway | No | Possibly, later | Yes, part of the roadmap |
| Engineering capacity to own governance long-term | Yes, we have room | Stretched but possible | Fully committed elsewhere |
| Score | Recommendation |
| 0 to 4 | Build is reasonable if scope stays small. Watch for scope creep. |
| 5 to 9 | Evaluate Boomi and comparable build or buy options seriously. |
| 10 to 14 | Buying is the safer path. In-house maintenance will use significant engineering resources. |
If you score high enough to buy, have a vendor evaluation checklist based on your top priorities:
- Traffic stays in your environment, not a vendor edge.
- Docs specify OSS versus Enterprise-gated features.
- Desktop client honors a base-URL redirect.
- Credentials are short-lived vault tokens.
- Every claimed feature has a shipping date in the current docs.
MCP is one piece of a bigger stack. LLM traffic and API calls need the same identity, policy, and audit controls, so a platform covering all three keeps governance from becoming three separate projects.
An MCP gateway handles tool invocation. It does not handle LLM traffic, the skills catalog agents load at runtime, or the API calls agents make outside MCP. Companies that finish an MCP gateway project often find themselves standing up an AI gateway not long after, then a skills catalog after that. Each brings its own governance, identity, and audit requirements. Getting all three to enforce the same policies is what turns three separate projects into one governance program, and running them as parallel control planes is what most teams end up doing by default.
The strategic question is bigger than whether to build or buy an MCP gateway. It is whether the platform you adopt covers the full agentic stack or forces you to solve identity, audit, and policy three separate times. Boomi’s enterprise platform combines an MCP Gateway for agents and tools with an AI Gateway for LLM traffic and an API Gateway for outbound calls, all sharing one policy, identity, and audit layer.
That unified footprint matters for compliance too. A single gateway governing MCP, LLM, and API traffic gives security review one artifact to evaluate instead of three separate reviews across products the company adopted at different times.
See how it all works together in the Boomi Platform How to Win: Orchestrate Your Business, Activate Your Data