Speakeasy vs Mintive: Which MCP gateway is right for the enterprise?

An enterprise MCP gateway has to do more than connect agents to tools. It has to decide what each person can do, stop sensitive data from crossing the tool boundary, and give administrators a precise way to resolve denied access.

That is why we recommend Speakeasy's MCP gateway over Mintive (formerly MintMCP). Speakeasy checks directory-linked permissions on each tool call, supports grants and explicit denies down to individual tools, and lets teams enforce built-in sensitive-data policies. Administrators can test contextual guardrails against real sessions and turn an authorization denial into a narrow grant.

MoonPay put this model into production across more than 200 MCP servers and 60,000 agent sessions. A 30-day proof of concept led to a company-wide rollout, with Okta-backed permissions by team, server, and tool, and unsanctioned MCP servers blocked by default. Read the MoonPay case study.

The short answer

Choose Speakeasy for an MCP gateway that gives you:

• Identity-bound tool grants: Check the person's directory-linked permissions on every call, with explicit denies that override broader access.
• Managed sensitive-data enforcement: Apply built-in detectors and deny matching tool calls without building a separate rule or middleware pipeline.
• Policy testing against real sessions: Replay contextual guardrails, review their decisions, and keep a scorecard before enforcing them.
• Precise access resolution: Turn a denied call into an Authorization Challenge that identifies the missing grant.
• Servers built from your own APIs: Generate a governed MCP server from an OpenAPI document instead of writing and hosting one by hand.

Mintive packages connectors and curated tools into Virtual MCP endpoints. Speakeasy puts the person's permissions and each tool call at the center of gateway policy, then gives administrators a direct way to test that policy and resolve denials without creating another endpoint for each access difference.

Speakeasy vs Mintive gateway comparison

Enterprise readiness and track record

Speakeasy has never lost a competitive evaluation to Mintive: every enterprise that shortlisted both products chose Speakeasy.

Speakeasy's gateway runs in production at companies with large, security-sensitive MCP estates. MoonPay's security operations team describes the change directly:

"Employees were connecting MCP servers we had no inventory of. Now every server runs behind the gateway, scoped by team and role, and anything unsanctioned is blocked by default."

Thierry Dang, Security Operations, MoonPay

Google, Fivetran, PlanetScale, LaunchDarkly, and Polar run MCP servers built on Speakeasy:

• Google moved the Gemini API SDKs to Speakeasy after its previous generation vendor was acquired and shut down, then built the Gemini Docs MCP server with Speakeasy on the same foundation. Google chose Speakeasy for continuity, on the commitment that Speakeasy would open source its generators so the tooling behind Gemini's SDKs and MCP server could not disappear again. The Docs MCP server gives coding agents current Gemini API documentation instead of stale training data, and ships pre-bundled in Antigravity.
• Fivetran exposed its Connector SDK and platform APIs as a hosted MCP server without spending weeks on infrastructure, an OAuth server, and client compatibility testing. Fivetran's Eli Davis calls Speakeasy's AI control plane "indispensable in enabling Fivetran's AI transformation."
• PlanetScale grew usage of its MCP server 44 times over in five months.
• LaunchDarkly built an MCP server that lets agents create feature flags, configure targeting rules, and manage rollouts.
• Polar moved from a local MCP server to a hosted one that turns a plain-language pricing description into a working billing setup.

Support is measured against service-level commitments rather than best effort. Speakeasy has met every response-time commitment across its support tiers, and 90% of support requests are answered in under 24 minutes.

Why choose Speakeasy as your MCP gateway over Mintive?

Authorize the person and the tool on every call

Speakeasy checks authorization when an agent connects to an MCP server and again when it calls a tool. Directory-linked roles can grant access to a server, a named tool, or a class of tools such as read-only actions. An explicit deny takes precedence over overlapping grants. A user can read invoices without gaining the ability to issue refunds through the same server.

The identity chain stays operational as teams change. Directory Sync receives Okta or Entra user and group changes through SCIM, checks the event stream about every 30 seconds, and applies membership and role changes in the same transaction. MCP user sessions use authorization code, PKCE, and consent, recording the human subject separately from the AI client. When a request reaches a remote server, Speakeasy removes the client's authorization and browser headers before applying the correct upstream credential. The client token never becomes a credential for the backend. See the remote-server request path.

For private systems, an outbound MCP tunnel puts the server on the same governed path without opening an inbound firewall rule.

Speakeasy can also restrict traffic to a custom-domain IP allowlist before a request reaches the server, limit admission to approved MCP clients, and encrypt stored credentials with customer-managed AWS KMS or Google Cloud KMS keys. These controls keep network access, client identity, and upstream secrets in the same gateway security model.

Mintive's RBAC pattern grants access to a Virtual MCP and curates the tools inside it. Its read-only and read-write example creates two Virtual MCPs over one connector. Speakeasy expresses that difference directly in the user's tool-level grant. See how Speakeasy authorizes a tool call.

Enforce sensitive-data policy with built-in detectors

Speakeasy's built-in detectors cover secrets, personal data, financial information, government identifiers, and healthcare data. A policy can inspect tool arguments and results, then deny a matching call. Security teams can put these controls on the MCP path without writing a middleware function or connecting an external classifier.

Policies can also inspect user prompts and assistant messages. Built-in categories for destructive tools, destructive CLI commands, and non-company accounts report activity after it happens, so Speakeasy treats those as detection rather than claiming they can block a completed action.

Mintive advertises PII redaction and secret blocking, but its managed scanner, Mint Guard, blocks only one category: prompt injection, and only at high confidence. Lower-confidence injection matches, credentials, personal data, and harmful content are logged while the call proceeds. Blocking or masking those categories requires a separate rule or custom middleware. Mint Guard also lets a call through when screening would exceed its timeout. Speakeasy's built-in detectors can deny matching calls directly, or warn and require confirmation, or quarantine the session. Administrators choose whether a prompt-based guardrail fails open or closed when its judge errors or times out. Explore Speakeasy guardrails.

Mint Guard also scans only the leading portion of a very large tool result and marks the scan incomplete. For sensitive-data policies, that makes the exact scanning and enforcement path worth examining, not just the presence of a detector.

Detection also creates a second exposure: the matched value itself. Speakeasy redacts a matched secret or personal identifier everywhere the finding travels after the call. Risk findings and Watchdog evidence show a redacted match, admins decide who may reveal it, and exclusion values are redacted in audit logs and webhook payloads. New OpenTelemetry destinations replace prompts, tool arguments, tool results, and user identifiers with [REDACTED] by default, so turning on SIEM export does not copy sensitive values into another system.

Test contextual guardrails against real activity

Speakeasy lets teams replay a proposed plain-language guardrail against recent agent sessions. Reviewers see each verdict and reason, mark it right or wrong, and keep that scorecard while refining the policy. The same scope applies during replay and live enforcement. That gives administrators a concrete basis for deciding when to move from logging to blocking.

Teams can set the audience by user or role, then narrow detection scope with CEL expressions to particular servers, tools, or arguments. They can exclude a known false positive without disabling the base detector. Actions range from logging and confirmation to denial or session quarantine; a quarantined session stays frozen until an admin releases it. The replay-and-scorecard workflow applies to prompt-based guardrails, while built-in detector policies use the same scope and action controls.

Mint Guard's Monitoring mode records detections and calls it would block. Speakeasy adds historical session replay and a persistent human-reviewed scorecard to the policy workflow. See the guardrail evaluation workflow.

Turn a denied call into a narrow grant

When Speakeasy rejects a tool call for missing permission, an Authorization Challenge records the person, server, tool, and required scope. An admin can open the challenge and grant exactly the access that was missing. The next attempt succeeds without granting an entire team a broader tool bundle. See Authorization Challenges.

Keep a large catalog behind one gateway URL

Speakeasy gives an agent one MCP URL for the servers it can reach. Instead of presenting every tool schema from every server at once, the gateway exposes four tools to discover servers, describe a server, fetch the schemas needed for a task, and execute a tool. As the catalog grows, the agent can find the right tool without carrying the entire catalog in its tool list. Each server still keeps its own authentication and access rules. The advantage is on-demand schema loading, not merely having a single endpoint. Explore Speakeasy's MCP gateway.

Teams can also publish per-team catalogs, so engineering, sales, and security each see the servers that apply to them. A common rollout starts with one client, such as Claude or Cursor, connected to one server, then widens team by team without each group waiting on the others.

Turn your own APIs into governed MCP servers

The tools that matter most usually sit behind a company's own APIs. Speakeasy can generate a tool for every operation in an OpenAPI document and publish the result as an MCP server on the gateway. Teams then curate that server: hide operations agents should never call, rename and re-describe tools so models choose them correctly, and tag tools so each client connects to a focused subset. Custom logic that no API covers runs as sandboxed TypeScript functions on the same server.

PlanetScale used this path to turn its database platform API into a production MCP server, so developers work with branches, schemas, and deploy requests from an agent instead of a dashboard. Fermat exposed its commerce API the same way, letting agents manage products, process orders, and coordinate fulfillment, and rolled out centrally managed MCP access to the whole team in two days.

Mintive's documented paths are approving servers from its catalog, connecting a remote server by URL, or hosting a server you already have as a STDIO configuration or Docker image. It has no documented path from an API contract to an MCP server, so an internal API needs someone to write, host, and maintain a server first.

Add modern sign-in to servers that lack it

Many MCP servers, including internal ones, were never built for OAuth. Speakeasy acts as the OAuth authorization server for gateway sessions, so clients get OAuth 2.1 with PKCE even when the upstream server supports nothing more than an API key. Clients can register dynamically or identify themselves with a Client ID Metadata Document published on their vendor's domain, and admins can restrict each server to approved clients. The agent never holds the vendor credential; the gateway keeps it and applies it upstream.

Sign-in runs through the identity provider the company already uses: Okta, Microsoft Entra ID, Auth0, WorkOS, Google Workspace, Ping Identity, or any SAML or OIDC provider. Claude, Claude Code, ChatGPT, Cursor, Copilot, Codex, and internal agents all connect the same way.

Beyond the gateway: enterprise AI governance

The gateway controls tool access. Speakeasy's AI control plane extends that identity, policy, and evidence into shadow MCP review, session investigation, cost analysis, and managed distribution of tools, Skills, and plugins.

Review shadow MCP use

Speakeasy inventories MCP servers found through supported device and client integrations, including remote URLs and local STDIO commands. Its shadow MCP access review gives reviewers an evidence snapshot: owner and domain history, authentication and requested scopes, declared tools, current users, registry history, and known advisories. Approval or denial records a reason. Approved servers receive daily checks for permission-relevant changes that can trigger re-review; blocked users can request scoped exceptions. Mintive's supported client hooks report off-gateway activity. Speakeasy connects that discovery to an auditable decision, drift check, and exception workflow.

Reviewers can add cited AI-assisted research to that evidence. When a user needs a blocked server, a short-lived request link or device notification opens an exception review; an approval can be limited to named people or roles. This turns an unapproved connection into a recorded ownership and access decision rather than a permanent blind spot.

Investigate risk, usage, and cost

Speakeasy Agent Sessions connect the person, client, transcript when enabled, tool calls, risk findings, tokens, and cost. Transcript access needs a separate chat:read grant, and each open is audited. Security teams can investigate findings through Watchdog, while OpenTelemetry export sends logs, metrics, and traces into their existing tools.

Full-session search and risk filters lead an investigator from a signal to the relevant tool arguments and result. Session capture and tool input/output logging start disabled, so teams choose when to collect that detail. Captured sessions can be exported as JSON for further investigation.

Watchdog groups related findings into ranked signals, so an analyst can see affected users and data types before opening the underlying session. Matched sensitive content stays redacted until an authorized reviewer reveals it; each reveal is audited. Analysts can turn a false positive into an exclusion without deleting the detector, or raise a real risk to a blocking policy.

Administrators can search audit logs by actor, action, and time, and use webhooks to send control-plane events into external workflows.

When capture is enabled, Speakeasy documents 90-day retention for tool logs and agent sessions. Mintive Agent Monitor defaults to seven days for metadata and full data, with configurable retention for enterprise customers. This matters when an investigation begins weeks after the original tool call.

Speakeasy attributes AI cost by user, role, department, cost center, model, client, account type, server, tool, and Skill, including supported activity outside a routed model gateway. It labels incomplete totals as estimates; a client with token counts but no reliable price does not silently contribute a fabricated cost. Mintive Agent Monitor also tracks usage and estimated cost, while its LLM Gateway budgets apply to traffic routed through that gateway.

Distribute approved tools and agent instructions

Speakeasy manages MCP servers alongside versioned Skills and plugins. Platform teams can publish a controlled capability, see adoption and cost, then update or roll back the artifact.

Skill versions are content-based and immutable. Teams can compare versions, track activation and feedback, and roll back a Skill whose instructions produce poor results. That connects tool governance to the instructions agents use to choose and call those tools.

Skill-content upload is on by default when Skills are enabled; administrators can turn it off to send only names, source details, hashes, users, and hostnames at activation. See the logging controls.

Speakeasy also records deployment history for managed MCP tools and supports retry or redeployment of an earlier version. Plugins package approved servers and Skills for Claude Code, Claude Cowork, Cursor, Codex, OpenCode, and OpenClaw. Mintive detects connector manifest changes and can keep newly discovered tools disabled; Speakeasy extends lifecycle management to the instructions and packages distributed alongside the tools.

Cover activity outside the MCP gateway

An MCP gateway sees routed tool calls, but employees also use local tools and AI clients outside that path. Speakeasy's device agent covers macOS, Windows, and Linux, deploying through Jamf Pro, Iru (formerly Kandji), Intune, ManageEngine, or Linux configuration management such as Ansible and Puppet. Inventory integrations show which managed devices are actually running the agent, and coverage can flow into Drata or Vanta as continuously tested compliance evidence. Mintive's MDM deployment covers macOS and Windows, so Linux developer machines and build hosts fall outside its endpoint monitoring. It can observe supported coding and desktop clients, while provider imports add post-event evidence from Anthropic, OpenAI, and Cursor. Anthropic hooks and LiteLLM integrations provide additional pre-inference policy points. Imported compliance events are for investigation, not retroactive blocking.

In Claude Code web, the device agent runs inside the hosted environment and reconciles required plugins and MCP configuration. In Cursor Cloud, project hooks capture agent activity. These integrations carry governance beyond a developer's laptop into supported cloud coding sessions.

Speakeasy vs Mintive feature comparison

Connecting MCP servers

Access control

Guardrails

Monitoring and investigation

Enterprise deployment and assurance

Speakeasy runs as a managed service or as a self-hosted deployment for customer-VPC, data-residency, and air-gapped requirements. Mintive's own pages disagree on self-hosting: its pricing page lists a self-hosted option, while its About page describes the product as "managed SaaS" with "no self-hosting".

Speakeasy's platform security documentation lists SOC 2 Type II and ISO 27001. Mintive's Trust Center lists SOC 2 Type 2, HIPAA, and CASA Tier 2. Buyers who require ISO 27001 will find it only on Speakeasy's list.

When Mintive may fit

Mintive is a reasonable choice for a narrower set of needs:

• You want Mintive to host and run third-party connectors for you, with no connector infrastructure on your side. Speakeasy also hosts servers, but Mintive's catalog of hosted connectors is its core offering.
• You want one vendor to route model traffic as well as tool traffic. Mintive's LLM Gateway, in early access, adds model allowlists, budgets, and switching between OpenAI, Anthropic, and Fireworks. Speakeasy governs model activity through Anthropic hooks, LiteLLM, and provider imports rather than acting as a model router.
• Your security team already runs a DLP classifier and wants MCP traffic sent through it with custom JavaScript middleware, and is prepared to own that code.
• GitHub Copilot CLI is a primary coding agent in your fleet and you want Mintive's local hooks on it.

If the priority is who can call which tool, what happens to sensitive data on that call, and how quickly an admin can fix a wrong decision, the sections above show where Speakeasy is stronger.

Why Speakeasy is the better choice

Put both products through the same gateway test: sync directory groups, allow a read tool while denying a write tool on the same server, send a sensitive-data payload, replay a contextual policy against previous sessions, and request access after a denial. These workflows make Speakeasy's advantages in policy granularity, direct enforcement, and administrator operations concrete.