Composio vs Kong AI Gateway for MCP: A head of engineering's comparison

TL;DR: Kong AI Gateway extends a proven API gateway to speak MCP, which works when your team already owns OAuth, token refresh, credential isolation, and action-level policy enforcement. Composio handles those layers as managed infrastructure with SOC 2 Type II and ISO/IEC 27001:2022 certifications. The free tier is generous: 100,000 tool calls per month, so you can test your first integration without a sales call.

Your team is three weeks into building OAuth flows for a new CRM integration, and no one has written a single line of agent logic yet. The MCP gateway decision you make this quarter determines whether that pattern repeats or whether you ship capabilities in days.

Kong AI Gateway extends a proven API gateway to speak MCP, which works when your team already owns OAuth, token refresh, credential isolation, and policy enforcement. Composio is built as action infrastructure for knowledge work agents: one governed path to act across business systems, with credentials isolated from the LLM context by design and policy-as-code evaluated in the request path before the model is involved. This comparison walks through the architectural differences that determine which approach fits your production requirements.

Core functions of an MCP gateway explained

An MCP gateway routes tool calls between AI agents and external APIs, manages authentication, enforces access policies, and logs activity. The implementation determines whether your team owns the authentication infrastructure or offloads it.

Traffic routing is what API gateways do well: accept a request, route it to an upstream service, return the response. Tool access management is what purpose-built MCP gateways do: resolve which credential to use, validate the action against policy, inject the credential into the outbound request, and log the outcome including denied calls.

The control plane defines policies and configurations, and the data plane executes tool calls. In an API gateway extension model, the control plane is the gateway admin API and the data plane is the request path. In a purpose-built MCP gateway, the control plane includes credential vaults, OAuth token lifecycle management, and policy-as-code evaluation, while the data plane executes tool calls through an isolated runtime.

In production, controlling agent access means defining which tools an agent can call, which actions it can take within those tools, which user accounts it can act on behalf of, and under what conditions. Access control must be enforced at the infrastructure layer, not through prompt instructions.

Comparing Composio and Kong for MCP

Kong AI Gateway is an API gateway with an MCP plugin extension. Composio is a purpose-built MCP gateway. The architectural difference shows up in credential handling, token lifecycle, policy enforcement, audit logging, and integration catalog depth.

Kong's strength is traffic routing and plugin extensibility for teams already operating Kong Gateway. Composio's strength is removing the credential management and policy enforcement burden from your engineering team.

The hidden costs of generic MCP gateways

Modern API gateways support OAuth flow management and token refresh, and AI-focused gateways now add tool-level ACLs with audit logging. What a generic gateway does not typically provide by default for MCP tool execution is credential isolation from LLM context.

A missing capability like this is an engineering task your team inherits. Building OAuth for three enterprise SaaS tools in-house creates three separate maintenance obligations, and each upstream API change lands directly on your engineering team's calendar.

How gateways handle tool execution flows

A tool execution flow follows these steps: the agent requests a tool call, the gateway resolves credentials, injects them into the outbound request, and returns the response. How each gateway handles these steps determines whether your team owns the authentication infrastructure.

Kong plugin limits for MCP

The Kong AI MCP Proxy plugin parses the MCP tool call and matches it to an OpenAPI operation, converts the operation into a standard HTTP request, sends the request to the upstream service, and wraps the HTTP response in MCP-compatible format. The Kong AI MCP Proxy plugin documentation describes this flow.

The Kong AI MCP OAuth2 plugin secures MCP traffic using OAuth 2.0 specification for MCP servers, ensuring only authorized MCP clients can access protected MCP servers. The plugin does not forward access tokens to upstream services by default, protecting against token theft or confused deputy attacks. Kong's MCP OAuth2 plugin is currently in Tech Preview per Kong's own documentation, which states it should not be used in a production environment. The Kong AI MCP OAuth2 plugin documentation describes this capability and its status.

Kong's plugin architecture extends the API gateway request/response model, and recent releases have closed part of the MCP gap. Kong AI Gateway 3.13 introduced MCP Tool ACLs, which evaluate each tool's ACL against the caller's Consumer Group at call time and reject unauthorized invocations before the request leaves Kong. Your team still configures and maintains these controls per integration inside the gateway's plugin model, while Composio evaluates policy-as-code on every tool call in the request path and resolves credentials inside an isolated runtime.

Composio's purpose-built MCP architecture

Composio's Proxy Execute routes all tool calls through server-side execution, so credentials stay out of agent memory and LLM context. Composio manages the full OAuth flow, including consent, token storage, and token refresh, with AES-256 encryption applied to stored credentials.

The server-side execution layer decrypts credentials inside the isolated runtime and injects them into the outbound HTTP header, with the response returned to the agent. The agent sees only the response and the calling application code never touches the raw credential string.

When an agent calls delete_lead on Salesforce, the gateway intercepts that call, evaluates whether the calling agent's role permits that specific action, resolves the correct credential inside an isolated runtime, and, if the policy check passes, forwards the request to the upstream MCP server. If the policy check fails, the gateway blocks the call and writes a denied-call record to the audit log before the server ever sees the request.

Execution and self-learning layers

Agents connected to many systems often load every tool definition into the context window, which crowds out the task itself. Composio keeps 50,000 tools in reach and zero in your context: the agent discovers and calls tools at runtime, so tool definitions and intermediate payloads stay out of the LLM context window. Bulk jobs, such as updating hundreds of CRM records, run as code in a sandbox rather than as hundreds of individual model-driven calls.

Integration catalog depth

Every new integration on a Kong-based gateway starts with building the MCP tool definition, the OAuth flow, and action-level policy enforcement, so the integration backlog grows with each customer request. Composio provides 1,500+ pre-built MCP integrations with specific action coverage, which turns a new connector request into a configuration task instead of a build.

Because each integration's actions are pre-defined and governed by policy-as-code, catalog breadth does not bypass access control. Admins permit or disable actions per user or role across connected apps, and Composio's managed OAuth layer handles authentication for each one. Custom builds are limited to niche or proprietary integrations.

Limitations of Kong for MCP agents

This credential isolation architecture is purpose-built for MCP, which highlights where an API gateway extension model stops. Kong's MCP plugin does not provide managed OAuth, token refresh automation, credential isolation from LLM context, or action-level policy enforcement within tools. Teams using Kong for MCP must build and maintain these layers themselves.

Action infrastructure for knowledge work agents

Each business system an agent acts on has its own OAuth flow, scope model, and refresh cycle. Composio provides one governed path to act across these systems, absorbing the per-integration auth work as managed infrastructure. Building that auth work in-house creates a maintenance obligation that grows with each new integration.

OAuth flow handling

Kong's plugin routes traffic but leaves OAuth consent, token storage, and scope management external to the gateway. Your team builds and maintains the OAuth implementation for each integration.

Composio's managed OAuth handles consent, token storage, refresh, and scopes for every user, customer, or employee.

Automating refresh for MCP gateways

Composio handles the full token lifecycle across 1,500+ connectors. Kong's MCP plugin documentation does not describe managed token refresh for upstream integrations, so teams should plan to own refresh logic per integration. Each in-house OAuth implementation is a maintenance obligation that grows when upstream APIs change their authentication models.

Multi-tenant credential isolation

Multi-tenant credential isolation means multiple users, customers, or employees each with their own connected accounts. Composio resolves which connected account to use per tool call, decrypts the credential inside an isolated runtime, and injects it into the outbound request. The credential is isolated from the LLM context and application code.

Kong's plugin documentation does not describe multi-tenant credential isolation as a built-in capability. Access tokens are not forwarded to upstream services by default, which protects against token theft, but your team may need to build the credential storage and isolation architecture.

Managing custom logic outside gateways

Both approaches require custom logic for business-specific requirements. The difference: Composio handles the commodity layers (OAuth, token refresh, credential isolation, policy enforcement) so custom logic is limited to business rules. Kong leaves the commodity layers as custom logic your team must build.

Granular access control and policy governance

An agent that can read Gmail should not necessarily be able to delete Slack messages. Access control must be enforced at the infrastructure layer, not through prompt instructions.

Prompt-based vs infrastructure-enforced guardrails

Prompt instructions are advisory and can be overridden by user input, while policy-as-code is evaluated in the request path and cannot be. Prompt-based guardrails are insufficient for enterprise access control because a sufficiently creative user input can override a model-level instruction. Infrastructure-enforced policies cannot be overridden by the model.

Defining granular action controls

Granular action controls look like this: an admin disables the "delete" action for a Slack integration. The agent cannot delete, regardless of what the prompt says, what the model reasons, or what a user tries to inject. Composio enforces this in the request path before the call is made.

Enforcing granular action-level controls

Composio enforces AI agent governance in the request path, before the model is involved. Admins set permitted actions per user or role through the dashboard, and policy-as-code evaluates every tool call before execution, so an agent cannot reason its way past a restriction and a prompt injection cannot widen its own scope.

Policy-as-code enforcement makes this check deterministic. The request reaches the Composio proxy layer and the request path runs policy evaluation before the outbound API call. Composio blocks the action, the agent receives an error response, and Composio logs the denied call with the invoking user ID, the tool, and the action attempted.

Kong's approach focuses on routing-level enforcement. Kong's plugin has default ACL and per-tool ACL blocks (v3.13+), which allow or deny specific Consumers or Consumer Groups. This is endpoint or tool-level access control, not action-level granularity (e.g., blocking only the "delete" action within a tool while permitting "read" and "create").

Delegating policy admin to Composio

Composio's dashboard lets admins set which actions are permitted per user or role. The request path enforces those restrictions as code, not by the model. This delegation means policy administration does not require engineering involvement for every change.

Quantifying engineering effort for connector updates

Building OAuth for three enterprise SaaS tools in-house creates three separate maintenance obligations. Each upstream API change lands directly on your engineering team's calendar.

The initial OAuth build figures come from two industry cost analyses: WorkOS estimates ~150 hours per integration, and Scalekit estimates 640-720 hours for AI agent OAuth.

Evaluating pre-built integration sets

Composio provides 1,500+ pre-built integrations with specific action coverage. Kong's plugin ecosystem provides API management, but MCP tool integrations are not pre-built. Each new integration with Kong requires building the MCP tool definition, OAuth flow, and action-level policy enforcement.

Building equivalent auth infrastructure yourself typically takes three to six months, with ongoing maintenance costs that compound as provider requirements change.

API action control and governance

Composio's specific actions per integration are pre-defined and governed by policy-as-code. Kong's API routes are governed by plugin rules, but action-level control within a tool requires custom implementation.

Mitigating third-party API changes

When an upstream API changes its authentication model or deprecates an endpoint, Composio's managed OAuth layer absorbs the change and Composio updates the connector catalog. Kong's plugin model requires your team to own the OAuth implementation and update it when the upstream API changes.

Composio isolates credentials in an AES-256 encrypted vault, enforces access policies in the request path before model involvement, and provides centralized credential governance across 1,500+ connected apps.

Custom integration build requirements

Both approaches require custom work for niche or proprietary integrations. The difference: Composio's catalog covers 1,500+ common apps, so custom builds are the exception. Kong's MCP plugin requires custom builds for every integration.

Audit logging and enterprise compliance posture

Prospects ask where credentials are stored, who can access them, and whether there is an audit log. The answer determines whether the deal moves or stalls, and the questionnaire usually lands on your senior engineers, pulling them off the roadmap until it is answered.

Audit trail features for MCP gateways

Composio's centralized audit log records every tool call with user, team, tool, action, and outcome, including denied calls. This provides a complete chain of custody usable as compliance evidence. Denied call entries follow the same structured format as successful ones, with status and metadata fields that indicate the call was blocked and why. For your sprint, that means audit evidence comes from a log that already exists, so no engineer has to build or backfill one before a security review.

Kong AI Gateway can apply security, governance, and observability controls to MCP servers, and Kong's AI MCP Proxy plugin documentation exposes a log_audits config flag that writes allowed and denied attempts to the audit log. The difference is operational: Kong's audit logging is a per-route plugin configuration your team enables and maintains, while Composio's centralized audit log is always on and records every call's user, team, tool, action, and outcome by default. For your engineering team, that means owning logging coverage on every route and confirming it is enabled before an audit asks for evidence.

Compliance standards for MCP gateways

Composio provides the action infrastructure layer with SOC 2 Type II and ISO/IEC 27001:2022 attestations.

Kong Inc. holds ISO/IEC 27001:2022 certification and maintains SOC 2 Type II attestation covering Kong AI Gateway and other Kong products. The Kong trust center describes these certifications.

Streamlining vendor security reviews

Composio's certifications and pre-filled compliance documentation help teams respond to enterprise questionnaires with structured, ready-to-share evidence, so senior engineers spend less sprint time assembling answers. Kong's gateway certifications help, but the credential handling and policy enforcement layers your team builds around the MCP plugin are not covered by Kong's certifications, so questions about those layers fall back on your engineers to answer.

When Kong MCP gateway is sufficient vs when you need Composio

Kong is sufficient when you already have OAuth infrastructure, but Composio handles the full OAuth lifecycle if you don't. Note that Kong's MCP OAuth2 plugin is currently in Tech Preview per Kong's own documentation and is not recommended for production use, so teams relying on it must plan their own production-ready OAuth layer. Kong works when you have a dedicated platform team to build and maintain credential handling and policy enforcement, but Composio provides these as managed infrastructure if your team needs to focus on product. Kong's traffic routing can cover a small integration footprint, but Composio's 1,500+ pre-built connectors become the faster path as your integration roadmap grows.

Kong MCP gateway operational gaps

The operational gaps are: no managed OAuth, no token refresh automation, no credential isolation from LLM context, no action-level policy enforcement, and audit logging that is a per-route plugin setting your team enables and maintains rather than a centralized, always-on log. Each gap is an engineering task your team inherits.

Limitations of native plugin support

Kong's plugin model extends the API gateway request/response model, but MCP tool execution requires credential resolution, scope validation, and action-level policy checks that are not native to the plugin architecture. Plugins extend the gateway but operate within the API gateway request/response model.

Criteria for dedicated MCP gateways

Quick self-assessment: Do you have 5+ integrations on your roadmap? Has an enterprise prospect asked about SOC 2 compliance or credential handling? Are senior engineers spending days on OAuth plumbing before writing agent logic? Do you need action-level policy enforcement that cannot be overridden by prompts? If yes to two or more, a dedicated MCP gateway is the right call.

Start on the free tier and test your first integration without a sales call. The 100,000 monthly tool call allowance covers a full proof of concept against real integrations before you commit to anything. If you want a security walkthrough first, book a call to review your requirements before the next enterprise review.

FAQs

Can Kong AI Gateway handle MCP workloads in production?

Yes, Kong's MCP plugin routes MCP traffic in production, but it leaves OAuth, token refresh, credential isolation, and action-level policy enforcement as engineering responsibilities your team must build and maintain.

What does Composio provide that Kong's MCP plugin does not?

Composio provides managed OAuth with full token lifecycle, credential isolation from LLM context by architecture, policy-as-code enforcement evaluated in the request path, and a centralized, always-on audit log that records every call's user, team, tool, action, and outcome, including denied calls, without per-route configuration.

Which option handles enterprise compliance better?

Composio holds SOC 2 Type II and ISO/IEC 27001:2022 certifications with pre-filled compliance packs covering credential handling and policy enforcement. Kong's gateway certifications do not cover the credential handling layers your team builds around the MCP plugin. For your engineering team, the difference is whether security questionnaires take days of senior engineer time or are answered with documentation that already exists.

What happens when an upstream API changes?

With Composio, the managed OAuth layer absorbs the change and Composio updates the connector catalog. With Kong's MCP plugin, your team owns the OAuth implementation and must update it when the upstream API changes.

Key terms glossary

MCP (Model Context Protocol): A protocol for connecting AI agents to external tools and data sources.

Policy-as-code: Access restrictions defined as code and evaluated in the request path before the model is involved.

Credential isolation: Architecture that keeps API tokens separate from LLM context and application code.

Token lifecycle: The full cycle of OAuth token issuance, refresh, and revocation.

Action-level policy: Access control that restricts specific operations within a tool, such as disabling delete actions.

Audit trail: A log of every tool call including user, team, tool, action, and outcome, including denied calls.