As AI agents connect to more enterprise tools, managing each connection separately can become difficult. Each system may require different authentication methods, expose different permissions, and introduce their own requirements for controlling what users and agents are allowed to do.
Natoma provides a centralized platform for managing those connections. It uses the Model Context Protocol (MCP) to connect AI agents and applications to enterprise data and tools while giving teams a central place to manage access, enforce policies, handle authentication and credentials, and maintain visibility into tool activity.
That centralized approach becomes especially useful as agents move beyond simple implementations. Direct connections to a few tools may be enough for some applications, while larger deployments may need more control over which tools users and agents can discover and invoke, which identities and permissions apply to those actions, how credentials are managed, and how activity is monitored or audited.
There are several approaches to solving this problem. Some platforms focus on authorization and governed tool execution, while others provide MCP gateways, agent identity infrastructure, managed integrations, or broader enterprise automation platforms. These approaches operate at different layers of the stack, affecting where policies are enforced, how agents authenticate to external systems, and how much integration infrastructure teams manage themselves.
Rather than treating every agent integration or MCP platform as interchangeable, this guide focuses on nine Natoma alternatives that represent different approaches to connecting and governing AI agents. By the end of this roundup, you'll understand how these platforms differ, the architectural and governance decisions behind them, and which approach best fits your AI application.
What Is Natoma?
Natoma is an enterprise platform for connecting AI clients and agents to enterprise tools and systems through the Model Context Protocol (MCP). It provides a verified library of MCP servers and supports custom MCP deployments across cloud, desktop, VPC, self-hosted, and on-premises environments.
A key part of Natoma's architecture is its managed endpoint. Organizations can make enabled MCP connections available across AI clients such as ChatGPT, Claude, Cursor, and internal agents through a single Natoma URL, providing a consistent way to distribute tool access across the organization.
Natoma also uses Profiles to package tools and skills for particular roles, intents, or functions. These predefined toolkits give organizations a structured way to provide different users and teams with the capabilities relevant to their work while managing distribution through the same platform.
Beyond its verified MCP library, Natoma can work with an organization's own infrastructure. Teams can bring custom MCP servers across multiple deployment environments and generate MCP servers from OpenAPI specifications, allowing proprietary applications and APIs to participate in the same MCP-based architecture.
The products in this guide are not identical replacements for Natoma. Some alternatives concentrate on particular parts of the architecture, such as agent authorization, MCP gateway infrastructure, identity, or managed integrations, while others provide a set of capabilities for connecting agents to enterprise systems.
How to Evaluate a Natoma Alternative
Natoma alternatives can overlap in functionality while taking different approaches to MCP infrastructure, authorization, identity, and tool access.
Before comparing individual products, these five considerations provide a useful framework for deciding which architecture fits your application.
Governance and Policy Enforcement
Start by looking at what the platform allows your organization to govern and where those controls are applied.
Some products place governance at a gateway between MCP clients and servers, while others apply authorization more directly to individual tools and actions. Depending on the architecture, controls may determine which servers or tools are available and what permissions are required before a tool can execute.
Consider how granular those controls need to be, what context can inform an authorization decision, and where in the request path you want governance to occur.
Identity and Authorization
Next, determine how the platform connects an agent's actions to the appropriate user or service identity.
For user-facing applications, an agent may need permission to act on someone's behalf in systems such as Gmail, Salesforce, or Slack. Arcade, for example, supports OAuth-authorized tool calls on behalf of individual users. Tools can request specific OAuth scopes, while Arcade manages the authorization flow and securely provides the resulting token when the tool executes.
Evaluate how each platform handles user and agent identity, delegated authorization, OAuth scopes, tokens, and connections to the identity systems your organization already uses.
MCP and Tool Management
The next question is how capabilities become available to agents.
Some platforms provide catalogs of prebuilt MCP servers and tools, while others let developers create custom tools or connect existing MCP infrastructure.
Consider how developers add and organize tools, connect existing services, control what capabilities agents can discover, and distribute those capabilities across AI applications.
Deployment Model
Deployment architecture determines where the components responsible for connecting agents and tools actually run. Depending on the product and configuration, those components may be vendor-managed or deployed within infrastructure controlled by the organization.
When comparing Natoma alternatives, verify where the relevant gateway or runtime runs, where tool traffic flows, which components your team operates, and whether the available deployment models fit your existing infrastructure.
Observability and Auditability
Finally, consider what the platform records about agent activity.
Useful audit data can include the identity behind a request, the AI client involved, the tool that was called, and the outcome. Natoma, for example, records structured audit information for tool calls and supports forwarding those logs to SIEM platforms for use by security teams.
Look at the information each platform captures, how teams can investigate that activity, and whether logs can connect with the monitoring and security systems your organization already uses.
The 9 Best Natoma Alternatives
1. Arcade
Best for: Teams that want an MCP runtime for connecting agents to tools with user authorization and centralized control over tool access.
Arcade is an MCP runtime for AI agents. It provides prebuilt and custom tools that agents can use to interact with services such as Gmail, Slack, GitHub, and Salesforce, while supporting authorization for actions performed on behalf of individual users. Developers can access these capabilities through MCP as well as Arcade's SDKs.
Its authorization model connects tool execution to the user whose permissions are required. Tools can declare the authorization they need, including OAuth scopes, and Arcade can manage the authorization flow and retain the resulting tokens for subsequent calls. When an authorized tool executes, Arcade makes the appropriate user token available to the tool.
Arcade also provides MCP Gateways that federate tools from multiple MCP servers into a single endpoint. Teams can choose which tools each gateway exposes and create different combinations for different agents or use cases. Existing remote MCP servers can be registered with Arcade, allowing selected tools from those servers to appear alongside other tools available within an Arcade project.
For teams building their own capabilities, Arcade provides tooling for creating custom MCP servers and tools, including tools that use authorization or secrets. Developers can run these servers themselves or deploy them to Arcade Cloud, where their tools become available within Arcade's tool catalog and can be included in MCP Gateways.
Why You Might Choose Arcade
- Centralizes governance across MCP tools, identity, and authorization.
- Federates tools from multiple MCP servers behind a single gateway endpoint.
- Lets teams control which tools are exposed through each gateway.
- Supports end-user authentication through existing OIDC identity providers.
- Manages OAuth authorization and required scopes for tools acting on users' behalf.
- Keeps OAuth tokens out of the MCP client and LLM.
Additional Highlights
Arcade offers multiple deployment options, including Arcade Cloud, deployments in your own cloud account, and self-hosting on Kubernetes. This gives teams flexibility in where the platform runs as their infrastructure requirements evolve.
2. MintMCP
Best for: Organizations that want a centralized MCP gateway for deploying servers, controlling tool access, and monitoring agent activity.
MintMCP is an agent governance platform with MCP Gateway and Agent Gateway products. Its MCP Gateway provides a centralized layer for connecting AI clients to MCP servers while managing authentication, access controls, server deployment, and activity monitoring.
Teams can host MCP servers through MintMCP, bring their own servers, and connect remote or open-source MCP servers. The platform also provides a private registry where organizations can curate approved MCP servers and manage which capabilities are available to their teams.
MintMCP uses Virtual MCPs, or VMCPs, to provide different groups with the tools appropriate for their work. Organizations can combine these with enterprise SSO through SAML/OIDC, SCIM group synchronization, centralized credential management, and granular permissions that can extend down to individual MCP server tools.
The platform also provides visibility into agent and MCP activity. MintMCP records contextual information about agent actions, including who initiated them, which tools were called, and what data flowed through the interaction. Audit records can also be exported to SIEM platforms or data lakes.
Why You Might Choose MintMCP
- Centralizes MCP deployment, access control, authentication, and monitoring.
- Hosts MCP servers and supports custom, remote, and open-source servers.
- Provides a private registry for curating approved MCP servers.
- Uses Virtual MCPs to provide different teams with role-based sets of tools.
- Supports enterprise SSO through SAML/OIDC and SCIM group synchronization.
- Provides granular access controls down to individual MCP server tools.
Additional Highlights
MintMCP includes sensitive-data protection that can detect PII and secrets in agent interactions. Teams can configure guardrails to block, flag, or alert on activity according to their policies, and MintMCP can integrate with existing DLP and SIEM tools.
3. Merge
Best for: Teams that want prebuilt MCP-ready connectors for giving AI agents authenticated, governed access to third-party services.
Merge Agent Handler is a tool-calling platform for AI agents that provides hundreds of prebuilt MCP-ready connectors across services such as Salesforce, Slack, Jira, GitHub, HubSpot, NetSuite, and Workday. Agent Handler implements an MCP server that lets agents discover and invoke tools across connected services without teams building each connector themselves.
Agent Handler associates credentials and tool activity with a Registered User, which represents an individual end user. When that user connects a third-party service, credentials are stored against their Registered User identity and used for subsequent tool calls. Depending on the application, Tool Packs can use individual credentials for each Registered User or shared credentials across users in the same Group.
Teams control the capabilities available to an agent through Tool Packs. Each Tool Pack bundles specific Connectors and tools for one agent surface, allowing organizations to create different sets of available actions for different agents, customer tiers, or environments.
Merge also places a Security Gateway in the tool-call path. Before a request reaches the third-party provider, the gateway scans tool arguments against configured data rules. Teams can allow, redact, or block matched values, while Tool Call Logs record executions with context including the Registered User, tool, arguments, result, status, latency, and any redactions that occurred.
Why You Might Choose Merge
- Provides hundreds of prebuilt MCP-ready connectors for third-party services.
- Supports per-user authentication and credentials shared across Groups.
- Uses Tool Packs to control which connectors and individual tools an agent can access.
- Scans tool arguments against configurable sensitive-data rules through its Security Gateway.
- Supports allow, redact, and block actions when configured data rules match.
- Records tool executions with contextual information for debugging and oversight.
Additional Highlights
Merge provides separate Tool Call Logs, API Request Logs, and an Audit Trail for different types of visibility. Tool Call Logs show what an agent invoked, API Request Logs show the underlying HTTP exchanges with third-party providers, and the Audit Trail records administrative and configuration changes within Agent Handler.
4. TrueFoundry
Best for: Organizations that want centralized MCP governance with granular access controls, credential management, and deployment options for private infrastructure.
TrueFoundry provides an MCP Gateway within its broader AI infrastructure platform. The gateway sits between AI clients and registered MCP servers, giving teams a central interface for making approved tools available to agents, developers, and applications. Teams can connect official remote MCP servers, register other remote servers, and deploy their own MCP servers through TrueFoundry.
Access is tied to identities managed through TrueFoundry or an organization's existing identity provider. The gateway can validate external identity-provider tokens from systems such as Okta and Azure AD and resolve them to a TrueFoundry user or virtual account. Administrators can then control which MCP servers and individual tools that identity is permitted to access.
TrueFoundry also separates authentication to the gateway from authentication to downstream MCP servers. For downstream access, teams can configure API keys with shared or individual credentials, OAuth 2.0, or token passthrough depending on the connected server. With OAuth Authorization Code flows, the gateway manages user consent, token storage, automatic refresh, and use of the appropriate token for subsequent requests.
For organizations managing tools across multiple servers, Virtual MCP Servers can combine selected tools from different MCP servers into one curated interface without requiring another deployment. Teams can then grant specific users or groups access to that collection of tools through the gateway.
Why You Might Choose TrueFoundry
- Centralizes access to registered MCP servers through an enterprise MCP gateway.
- Applies permissions at both the MCP server and individual tool level.
- Integrates with external identity providers such as Okta and Azure AD.
- Supports API keys, OAuth 2.0, and token passthrough for downstream MCP authentication.
- Creates Virtual MCP Servers from selected tools across multiple MCP servers.
- Provides a centralized registry for managing registered MCP servers.
Additional Highlights
TrueFoundry supports deployments in VPC, on-premises, air-gapped, and multi-cloud environments. This gives organizations flexibility to run the platform within infrastructure they control and align the deployment with their existing cloud and security architecture.
5. Kong
Best for: Teams that want to govern MCP traffic within a gateway architecture that can also support APIs, LLMs, and agent-to-agent communication.
Kong AI Gateway extends Kong's gateway architecture to AI and agentic traffic. For MCP, Kong can proxy existing MCP servers or create MCP interfaces from existing APIs, giving teams a centralized point for applying authentication, access controls, traffic policies, observability, and other gateway capabilities to MCP traffic.
Kong's AI MCP Proxy plugin can convert existing API operations into MCP-compatible tools. It can also aggregate tools backed by multiple APIs behind a single MCP server endpoint, allowing organizations to make existing services available to MCP clients without building separate MCP server implementations for each API.
The same plugin supports granular access controls for MCP tools. Teams can define default or per-tool allow and deny rules based on authenticated Kong Consumers, Consumer Groups, or OAuth access-token claims, depending on the configuration. Kong can also generate audit logs for these access-control decisions.
Kong also offers MCP Registries through Konnect Catalog, providing a centralized publishing and discovery endpoint for MCP servers within an organization. The registry can catalog server definitions and their available package or remote connection options.
Why You Might Choose Kong
- Governs MCP traffic through the same gateway platform used for API and AI traffic.
- Converts existing API operations into MCP-compatible tools.
- Aggregates tools backed by multiple APIs behind a single MCP server endpoint.
- Applies default and per-tool access controls to MCP tools.
- Uses Kong Consumers, Consumer Groups, or OAuth token claims to inform tool access rules.
- Provides MCP-specific metrics, audit logs, and other observability capabilities.
Additional Highlights
Kong AI Gateway also supports Agent-to-Agent (A2A) protocol traffic through its AI A2A Proxy plugin, which provides protocol-aware observability and control. Teams can apply Kong authentication plugins to A2A routes, providing a consistent gateway architecture as applications expand from tool access through MCP to communication between agents.
6. Solo.io / agentgateway
Best for: Teams that want an open-source gateway for MCP, A2A, LLM, and other agentic traffic.
Agentgateway is an open-source gateway for connecting, securing, and observing communication between AI applications, agents, models, and tools. Created by Solo.io and donated to the Linux Foundation, the project is licensed under Apache 2.0 and can run as a standalone gateway or within Kubernetes. It provides protocol-aware handling for MCP and Agent-to-Agent (A2A) traffic.
For MCP, agentgateway can aggregate multiple MCP servers behind a single endpoint. It supports stdio, SSE, and Streamable HTTP connections to MCP servers and can expose operations from existing APIs as MCP tools using an OpenAPI specification. This gives teams several ways to connect existing services and MCP infrastructure through the same gateway layer.
Agentgateway also provides MCP-specific authentication and authorization. It supports OAuth 2.0 protection for MCP servers with JWT validation, while CEL-based authorization rules can control access to tools, prompts, and resources. When a capability is not authorized for a client, agentgateway can filter it from MCP list responses so that the client does not discover it.
The gateway includes MCP-aware observability through metrics, logs, and distributed tracing. Teams can use this telemetry to understand MCP requests and tool interactions as traffic passes between clients and connected servers.
Why You Might Choose agentgateway
- Aggregates multiple MCP servers behind a single gateway endpoint.
- Supports stdio, SSE, and Streamable HTTP connections to MCP servers.
- Exposes operations from existing APIs as MCP tools using OpenAPI specifications.
- Provides OAuth 2.0 protection and JWT validation for MCP servers.
- Applies CEL-based authorization rules to MCP tools, prompts, and resources.
- Includes MCP-specific metrics, logs, and distributed tracing.
Additional Highlights
Agentgateway also supports the Agent-to-Agent (A2A) protocol, giving teams a gateway for communication between agents as well as connections between agents and MCP tools. This allows the same gateway architecture to support multiple forms of agentic traffic as AI systems expand.
7. Descope
Best for: Teams that want identity-focused infrastructure for authenticating AI agents, securing MCP servers, and governing access to tools and downstream services.
Descope's Agentic Identity Hub provides identity and access infrastructure for AI agents, APIs, and MCP servers. Descope can act as the OAuth 2.1 authorization server for APIs and MCP servers, issuing scoped tokens that let organizations connect agent activity to users, tenants, or autonomous agent identities.
For MCP servers, Descope supports OAuth 2.1 authentication, client registration, user consent, and tool-level scopes. Policies can use runtime context to determine which resources and scopes an agent can access, including information about the agent, user, tenant, roles, JWT claims, and requested resource.
Descope also provides Connections for managing credentials used to reach downstream services. Connections can securely store OAuth tokens and API keys at the user or tenant level, with Descope managing storage and refresh. Teams can place an MCP server, gateway, or other Resource between the agent and the Connections vault so downstream credentials can be retrieved when tools execute without placing long-lived third-party secrets in the agent itself.
The Agentic Identity Hub also provides a centralized view of agentic identities and their access. Organizations can associate agents with users and tenants, manage the resources and scopes available to them, and record events such as agent registrations, token issuance, policy decisions, and credential access in audit logs.
Why You Might Choose Descope
- Provides identity and access infrastructure for AI agents and MCP servers.
- Acts as an OAuth 2.1 authorization server for MCP servers and APIs.
- Supports tool-level OAuth scopes and policy-based access controls for agents.
- Evaluates policies using context such as agent, user, tenant, role, JWT claim, and resource information.
- Stores and manages OAuth tokens and API keys for downstream services through Connections.
- Works alongside existing workforce identity providers while adding identity controls for agents.
Additional Highlights
Descope supports step-up authentication for sensitive agent actions. Using human-in-the-loop flows, teams can require additional user approval before an agent receives time-bound access with elevated scopes, providing an additional verification step for workflows that call for it.
8. Composio
Best for: Developers that want agents to discover and use tools across many applications with per-user authentication and managed execution.
Composio provides tool and authentication infrastructure for AI agents. Its architecture centers on Sessions, which provide the runtime context for an agent acting on behalf of a user. Each Session ties together the user, available toolkits, authentication, and connected accounts so the agent can discover and execute tools within that scoped environment.
Sessions can provide access to Composio's toolkit catalog or be restricted to specific toolkits and individual tools. By default, agents receive a small set of meta tools that can discover, authenticate, and execute application tools at runtime instead of loading hundreds of tool definitions into the model's context. Teams can also configure a fixed set of tools when they want an agent to work with predefined capabilities.
Authentication is organized around users and their connected accounts. Each connected account stores the credentials needed to access a toolkit, while Composio handles credential management and token refresh. Hosted Connect Links let users authenticate to external applications, and credentials never pass through the application or model.
Composio can also expose a Session through a hosted MCP endpoint. The MCP endpoint uses the same Session configuration as Composio's native tools, including its toolkits, authentication settings, and connected accounts. This lets MCP-compatible clients access a configured set of capabilities through a single Session-based endpoint.
Why You Might Choose Composio
- Creates per-user Sessions that combine tools, authentication, and connected accounts.
- Supports runtime tool discovery across enabled toolkits.
- Lets teams restrict Sessions to specific toolkits or individual tools.
- Manages user credentials and OAuth token refresh for connected accounts.
- Provides hosted Connect Links for authenticating users with external applications.
- Exposes Sessions through hosted MCP endpoints for MCP-compatible clients.
Additional Highlights
Composio supports multiple connected accounts for the same toolkit, such as separate work and personal Gmail accounts. Teams can enable multi-account mode, assign aliases to individual accounts, and configure whether an agent must explicitly select which account to use for a tool call.
9. Workato
Best for: Organizations that want to expose existing integrations, workflows, and business logic to AI agents through managed MCP servers.
Workato provides Enterprise MCP as part of its broader orchestration platform. Teams can create Workato-hosted MCP servers that expose business capabilities as tools for MCP-compatible AI clients. MCP servers can be created from scratch or installed from Workato's catalog of prebuilt server templates.
When creating a server from scratch, teams can use project assets or API collections as the source for its tools. Supported project assets include recipe functions, API recipes, and skills, allowing organizations to make existing automation and integration logic available through MCP. Workato can also connect third-party MCP servers through MCP proxy.
Workato provides controls for managing how MCP servers are accessed and used. Teams can configure available tools and apply controls such as user provisioning, rate limits, usage quotas, and IP restrictions. MCP server logs include information such as the request IP address and the ID of the user who made the request, providing visibility into server activity.
For workflows that should preserve individual user permissions, Workato provides Verified User Access. Supported recipe functions and API recipes that use the OAuth 2.0 authorization code grant can execute with an end user's own connection, allowing downstream actions to use that person's identity and permissions.
Why You Might Choose Workato
- Exposes recipe functions, API recipes, skills, and API collections through MCP.
- Provides Workato-hosted MCP servers for MCP-compatible AI clients.
- Lets teams configure the individual tools available through their MCP servers.
- Connects third-party MCP servers through MCP proxy.
- Provides controls such as user provisioning, rate limits, usage quotas, and IP restrictions.
- Supports end-user credentials for eligible tools through Verified User Access.
Additional Highlights
Workato provides prebuilt MCP server templates that teams can customize for their own workflows. Organizations can add, modify, or remove tools and incorporate business logic such as validation steps, conditional routing, and approval flows through skill recipes.
Which Natoma Alternative Should You Choose?
Choose Arcade if...
You want an MCP runtime with governance centered on identity, authorization, and controlled access to tools.
Choose MintMCP if...
You want a centralized MCP gateway for managing approved servers, tool access, enterprise identity, credentials, and auditing.
Choose Merge if...
You want prebuilt MCP-ready connectors that give agents authenticated access to third-party services with tool controls and configurable sensitive-data rules.
Choose TrueFoundry if...
You want centralized MCP governance with granular server- and tool-level access controls, credential management, and deployment options for private infrastructure.
Choose Kong if...
You want to govern MCP traffic within a broader gateway architecture that can also support APIs, LLMs, and agent-to-agent communication.
Choose agentgateway if...
You want an open-source gateway for MCP, A2A, LLM, and other agentic traffic that can run independently or within Kubernetes.
Choose Descope if...
You want identity-focused infrastructure for authenticating agents, securing MCP servers, managing downstream credentials, and applying authorization policies.
Choose Composio if...
You want agents to discover and use tools across many applications with per-user authentication, managed execution, and hosted MCP access.
Choose Workato if...
You want to expose existing integrations, workflows, and business logic to AI agents through managed MCP infrastructure.
