A platform team rolls out an MCP gateway because the sprawl finally got out of hand. Every engineer had wired Claude, Cursor, and ChatGPT into a personal collection of MCP servers — GitHub, Slack, Notion, a couple of internal ones — each authenticated with a personal token pasted into a config file nobody was tracking. Speakeasy solves exactly this. One URL, every assistant points at it, and now there is a single place where identity, access, and audit live. When an agent tries to call a tool with a payload carrying PII, the gateway redacts it before the request reaches the downstream server. That is real, synchronous enforcement, and it happens at precisely the layer where a lot of AI risk actually enters an organization: the tool call.

Then a different question comes up in the security review. Half the team's agents aren't reaching tools through the gateway at all — they're internally built agents making direct LLM calls, running multi-step reasoning loops, and burning budget on their own. The gateway sees the MCP traffic it brokers. It doesn't see the agent's reasoning, its per-run cost curve, or the tool calls that never route through an MCP server. The gateway solved the tool-access problem for assistants the team didn't build. It didn't govern the agents the team did build, because that was never the gateway's vantage point.

That is the shape of this comparison. It isn't better-versus-worse at the same job. Speakeasy governs traffic that flows through an MCP gateway, and it does that well. Waxell governs the same gateway traffic and the agent execution layer beneath it — and it does so from a self-serve, transparently priced entry point rather than an enterprise sales motion.

Speakeasy is an AI control plane built around an MCP gateway: every AI agent points at one URL, and the gateway brokers, secures, and observes their calls to a catalog of MCP servers, with runtime guardrails that block PII and prompt injection before a call reaches its target. Waxell is also a control plane, but its governance surface is broader — an MCP Gateway that does the same gateway-layer enforcement, plus two-line SDK instrumentation that governs the agents you build at the execution level, across 50+ policy categories. Speakeasy answers "is this MCP tool call allowed?" Waxell answers that same question and "is this agent, on this run, allowed to do what it's about to do?" — and lets you start for free instead of starting with a sales call.

What is Speakeasy built for?

Speakeasy began as an API-tooling company — OpenAPI-native SDK generation, Terraform providers, CLIs, and contract tests, a product line it still sells as "SDKs & CLIs." Over the last year it repositioned its primary pitch to "The AI control plane to connect, secure, and govern every agent," anchored by a dedicated MCP Gateway product whose tagline is "Your MCP Gateway. Connect. Secure. Observe." This is a real strategic pivot, not a bolted-on feature, and it puts Speakeasy in direct competition with the MCP-gateway half of Waxell's platform.

The gateway is a genuine single entry point. Point Claude, Cursor, ChatGPT, Copilot, and internal agents at one URL, and the gateway brokers access to a catalog of MCP servers — pre-built SaaS integrations (GitHub, Slack, Notion, Gmail, Linear, Airtable, Asana, Figma, AWS, Amplitude, Snowflake, and more), customer-imported TypeScript or Python servers, or servers generated from an OpenAPI spec. That OpenAPI-to-MCP generation path is a natural extension of Speakeasy's origins and a real convenience for teams that already live in API specs.

The runtime enforcement language is unusually explicit. Speakeasy's own product page states that its runtime guardrails deliver "PII redaction, prompt injection detection, and shadow-tool blocking on every tool call before it reaches an MCP server or your data." That "before it reaches" phrasing is unambiguous pre-execution enforcement — stronger and more direct than many competitors that only imply real-time blocking.

Identity and audit are first-class. SSO plugs into one place, with OAuth 2.1, DCR, and PKCE available even when the upstream MCP provider doesn't natively support them. Role-based access scopes down to the server, toolset, or individual tool, and teams can be provisioned sub-catalogs so each sees only what it should. Every tool call, permission change, and access event is logged and searchable, and the platform advertises SOC 2 Type II and ISO 27001 certification out of the box. On the observability side, the gateway offers real-time logs, distributed tracing across agents and downstream APIs, cost and usage attribution by team, and anomaly detection for shadow tools and runaway agents.

For an organization whose main problem is ungoverned assistant-to-tool traffic, this is a coherent and well-built answer.

Where does Speakeasy's scope end?

None of this is a flaw in what Speakeasy set out to build. It's the boundary of a gateway-centric control plane, drawn exactly where agent-execution governance would need to begin.

The vantage point is the gateway, not the agent. Speakeasy governs what flows through the MCP gateway. An internally built agent making direct LLM calls, running a reasoning loop, or invoking tools that don't route through an MCP server operates outside that vantage point. The gateway can't halt a session that crosses a per-run cost threshold if that session's spend never passes through it, and it doesn't instrument the agent's own code the way an SDK does. Its governance is as complete as your traffic's routing through it is complete.

Enforcement is scoped to MCP-layer concerns. PII redaction, prompt injection detection, and shadow-tool blocking are the guardrails on offer — genuinely valuable, and aimed squarely at the tool-call boundary. Broader policy categories evaluated at the agent-execution level — content, safety, quality, reasoning, rate-limiting, scheduling, kill switches tied to the agent rather than the tool — are outside the gateway's remit.

Pricing is fully enterprise-gated. Speakeasy's pricing page is sales-gated end to end — "Tailored. Every AI transformation is different. Let's Chat." There is no self-serve tier and no published dollar figures for either the AI Control Plane or the SDKs & CLIs line; the compare-plans grid resolves to a single "Enterprise" column. For a large organization with a procurement process, that's expected. For a smaller team or an individual developer who wants to try governance before committing to a contract, it's a real barrier to entry.

It's one surface, not a spanning platform. Speakeasy governs assistants and agents at the MCP gateway. It doesn't extend to discovering and governing shadow AI on employee laptops, or to a hardened execution runtime for high-stakes workflows. Those are separate problems that a gateway, by design, doesn't reach.

What Waxell adds

Waxell meets Speakeasy directly at the gateway and then keeps going. Waxell's MCP Gateway provides the same one-URL-per-tenant entry point, brokering 160+ upstream connectors with PII redaction in flight, secret blocking (secrets never leave the gateway), a prompt-injection scanner that inspects tool descriptions at fingerprint time before any agent calls them, human-in-the-loop approvals for destructive actions, three identity/auth modes with one-transaction offboarding, and a durable audit log with CSV export. It adds tool fingerprinting with five states — Pending, Drift, Trusted, Blocked, Removed — so a server that silently changes its tool definitions is caught as drift rather than trusted by default. Policy changes propagate in about 30 seconds, and the same container image can run self-hosted in a customer VPC. At the gateway layer, this is a feature-for-feature match, with drift detection and secret handling as points of difference.

The broader difference is everything beneath the gateway. Waxell's Observe SDK instruments the agents you build with two lines of code and no rebuilds, capturing the full trace — every model call, tool invocation, cost, and timing — and then governs that same execution against 50+ policy categories: cost, content, safety, quality, rate-limiting, kill switches, and more. That's governance at the agent-execution level, not only at the tool-call boundary, and it applies whether or not the agent's traffic ever touches an MCP gateway. Waxell Runtime extends this to governed execution for high-risk workflows where policies gate each step before it runs, and Waxell Endpoints discovers and governs AI tools running locally on employee devices. Per its own /compare positioning, Waxell is the only vendor spanning all four market tiers — observability-plus-governance, developer eval, agent security, and lightweight gateway — where Speakeasy sits primarily in the gateway tier it has staked out well.

And the entry point is different in kind. Waxell is free to start with a two-line setup and transparent, published pricing tiers, rather than a custom quote behind a sales conversation.

Feature comparison

Three scenarios, two different reaches

The cleanest way to separate these two is by where the governance boundary sits in a given situation.

Scenario: your whole company uses assistants that reach into SaaS tools, and you need one governed surface in front of all of it.

• Speakeasy: This is its core case. Point every assistant at the gateway, get SSO, RBAC, runtime guardrails, and a searchable audit trail on every MCP call. It's purpose-built for exactly this.

• Waxell: The MCP Gateway covers the same ground, with tool fingerprinting and drift detection and secret blocking layered in — and you can turn it on self-serve rather than through procurement.

Scenario: your team builds its own agents, and you need to govern their cost, content, and behavior at the execution level.

• Speakeasy: The gateway governs the MCP tool calls those agents make. Reasoning, direct LLM calls, and per-run cost that don't route through the gateway sit outside its view.

• Waxell: Two-line SDK instrumentation captures and governs the agent's full execution against 50+ policy categories, independent of whether traffic passes through a gateway.

Scenario: you want to start small, prove value, and expand — without a contract up front.

• Speakeasy: Pricing is enterprise-only and sales-gated; there is no self-serve path to try it first.

• Waxell: Free to start with a two-line setup and published tiers, so a single team can adopt governance before it becomes an organization-wide commitment.

When to use Speakeasy

• Your primary problem is ungoverned assistant-to-tool traffic, and you want one gateway that brokers, secures, and observes every MCP call across the org.

• You value Speakeasy's explicit pre-execution guardrails at the tool-call boundary and want SSO, RBAC, and audit concentrated at the gateway.

• Your organization also needs OpenAPI-native SDK, CLI, or Terraform-provider generation from the same vendor — Speakeasy's original and still-strong product line.

• You're comfortable with enterprise-only, custom-quote pricing and have a procurement process to work through.

When to use Waxell

• You need governance that reaches past the MCP gateway to the agents you build — SDK-level instrumentation and 50+ policy categories evaluated at execution, not only at the tool call.

• You want a self-serve entry point with transparent, published pricing rather than a fully sales-gated model.

• You want gateway-layer features Speakeasy doesn't surface distinctly — tool fingerprinting with drift detection, secret blocking, and human-in-the-loop approvals — alongside the broader lifecycle.

• You need more than one surface: governed execution for high-risk workflows (Runtime) and shadow-AI discovery on employee devices (Endpoints), in addition to the gateway.

How Waxell handles this: Waxell operates as an AI control plane that governs both the gateway and the agent. The MCP Gateway puts one governed URL in front of 160+ upstream connectors, redacting PII in flight, blocking secrets before they leave, scanning tool descriptions for prompt injection at fingerprint time, and tracking every tool through a five-state trust model that catches silent drift. Beneath it, the Observe SDK instruments the agents you build in two lines and enforces 50+ policy categories at the execution level — cost, content, safety, kill switches — whether or not that traffic ever routes through a gateway. It's the same synchronous, pre-execution enforcement Speakeasy applies at the tool call, extended across the full agent lifecycle, and available to start for free.

Weighing an MCP gateway and want governance that reaches the agents you build, not just the tools they call? Get started with Waxell.

Frequently Asked Questions

Is Waxell a Speakeasy alternative?

Yes, and a broader one at the gateway layer. Waxell's MCP Gateway matches Speakeasy's core gateway capabilities — one URL per tenant, PII redaction, prompt injection scanning, RBAC, SSO, and audit — and adds tool fingerprinting with drift detection, secret blocking, and human-in-the-loop approvals. Beyond the gateway, Waxell also instruments and governs the agents you build at the execution level, which a gateway-centric product doesn't reach. Teams whose problem is purely assistant-to-tool traffic may find Speakeasy's gateway sufficient; teams that also build their own agents generally need execution-level governance too.

What is the main difference between Speakeasy and Waxell?

Scope and entry point. Speakeasy governs traffic that flows through its MCP gateway. Waxell governs the same gateway traffic and the agent-execution layer beneath it — via a two-line SDK and 50+ policy categories — and it does so from a self-serve, published-pricing starting point rather than an enterprise sales motion.

Does Speakeasy enforce policy in real time, or just observe?

It enforces in real time at the gateway. Speakeasy's product page describes runtime guardrails that redact PII, detect prompt injection, and block shadow tools "on every tool call before it reaches an MCP server or your data" — explicit pre-execution enforcement. The limit is vantage point: that enforcement applies to calls routed through the gateway, not to agent behavior that never passes through it.

Can I use Speakeasy and Waxell together?

You can, though their gateway layers overlap heavily, so most teams would pick one gateway. A more common pairing is Speakeasy's original SDK/CLI/Terraform generation line alongside Waxell's execution-level governance, since those solve genuinely different problems. If you're choosing a single MCP gateway, the decision comes down to whether you also need execution-level agent governance and a self-serve entry point — where Waxell's scope is wider.

How does Speakeasy's pricing compare to Waxell's?

Speakeasy is enterprise-only and sales-gated, with no self-serve tier and no published dollar figures — its pricing page resolves to a single "Tailored — Let's Chat" enterprise column (verified live on 2026-07-24). Waxell is free to start with a two-line setup and publishes its pricing tiers, which lowers the barrier for a single team to adopt governance before committing organization-wide.

Sources

• Speakeasy, MCP Gateway product page (2026) — https://www.speakeasy.com/product/mcp-gateway

• Speakeasy, Pricing (2026) — https://www.speakeasy.com/pricing

• Speakeasy, AI control plane resource (2026) — https://www.speakeasy.com/resources/ai-control-plane/

• Speakeasy, homepage (2026) — https://www.speakeasy.com/

• Waxell, waxell/competitor-intel/speakeasy.md research brief (researched 2026-07-13)