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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Simplifies AI agent integration with complex APIs by providing a standardized MCP interface.
Biggest con
Reliance on JMESPath for output mapping might require a learning curve for some users.
TL;DR - API to MCP
- Transforms REST/GraphQL APIs into hosted MCP servers for AI agents.
- Offers visual builder and AI agent integration for server creation and management.
- Supports diverse authentication methods and secure credential handling for real-world APIs.
Pricing: Free plan available
Best for: Growing teams
What is API to MCP?
API to MCP provides hosted MCP (Multi-Modal Communication Protocol) servers that allow AI agents and large language models to interact with real-world APIs. It transforms REST and GraphQL APIs from public services, SaaS platforms, and internal business systems into remote HTTP MCP servers. The platform handles authentication (OAuth, API key, Bearer token, Basic Auth), workflow tools, encrypted credentials, and JMESPath output mapping to provide clean, AI-readable JSON responses.
Users can build these MCP servers either through a visual dashboard for hands-on control or via an AI Agent Builder, allowing coding agents to create, update, test, and deploy servers from chat. This enables businesses to expose internal systems like CRM, ERP, HR, finance, and marketing platforms to employees through controlled MCP tools, or to integrate with external services like payment gateways, developer tools, and public data sources, all while ensuring secure credential management and streamlined agent interaction.
Pros & Cons
Pros
- Simplifies AI agent integration with complex APIs by providing a standardized MCP interface.
- Offers flexible server creation methods, catering to both visual and agent-driven workflows.
- Ensures high security for API credentials with encryption and masking.
- Supports a wide range of real-world API types and authentication mechanisms.
- Enables creation of multi-step workflow tools for agents.
Cons
- Reliance on JMESPath for output mapping might require a learning curve for some users.
- The number of active MCP servers and API calls are limited on lower-tier plans.
- Advanced enterprise features and custom limits require direct contact, indicating potential complexity for large-scale deployments.
Key Features
Hosted MCP server deploymentVisual MCP builder for configurationAI Agent Builder for agent-driven server creationSupport for REST and GraphQL APIsMultiple authentication methods (OAuth, API Key, Bearer Token, Basic Auth)Workflow tools to combine multiple API callsJMESPath for structured output mappingEncrypted credentials and masked secrets
Pricing Plans
Pricing checked Jul 9, 2026
Free
$0 / month
Everything in all plans, plus:
- 1 active MCP servers
- 3,000 API calls/month
- 15 tools per server
Starter
$6.99 / month
Everything in all plans, plus:
- 3 active MCP servers
- 10,000 API calls/month
- Unlimited tools per server
- Workflow tools
- OAuth Authorization Code
- 30 OAuth user connections
Professional
$20.99 / month
Everything in all plans, plus:
- 15 active MCP servers
- 50,000 API calls/month
- Unlimited tools per server
- Workflow tools
- OAuth Authorization Code
- 300 OAuth user connections
Business
$41.30 / month
Everything in all plans, plus:
- Unlimited active MCP servers
- Unlimited API calls
- Unlimited tools per server
- Workflow tools
- OAuth Authorization Code
- 3,000 OAuth user connections
- Priority support
Included in all plans
- OAuth Client Credentials
- Visual MCP builder
- AI agent integration
- Analytics dashboard
How API to MCP's pricing compares
At $6.99/mo, API to MCP is the most affordable of its 4 direct competitors.
Entry paid plan, monthly. Pricing checked Jul 9, 2026.
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API to MCP FAQ
How does API to MCP facilitate AI agent interaction with diverse APIs?
API to MCP transforms various REST and GraphQL APIs into remote HTTP MCP servers, enabling AI agents and large language models to interact with real-world services. It handles authentication, workflow tools, and provides AI-readable JSON responses through JMESPath output mapping.
Which teams would benefit most from using API to MCP?
Teams looking to integrate AI agents with internal business systems like CRM, ERP, HR, finance, and marketing platforms would benefit. It also serves teams needing to connect AI agents with external services such as payment gateways, developer tools, and public data sources.
How does API to MCP compare to a tool like LangChain?
API to MCP focuses on providing hosted MCP servers to standardize AI agent interaction with any API, including handling authentication and output mapping. LangChain, conversely, is a framework designed for developing applications powered by large language models, offering tools for chaining together different components.
What kind of limitations should users be aware of when using API to MCP?
Users should note that reliance on JMESPath for output mapping may present a learning curve for some. Additionally, lower-tier plans have limits on the number of active MCP servers and API calls, and advanced enterprise features require direct consultation.
Can API to MCP be used to automate multi-step workflows for AI agents?
Yes, API to MCP allows users to create multi-step workflow tools that AI agents can utilize. This enables agents to perform complex sequences of actions across different integrated APIs.
How is API to MCP priced?
API to MCP is available on a free tier, which offers basic usage. Paid plans are available for users who require more extensive usage and additional features.
Does API to MCP provide secure handling of API credentials?
Yes, API to MCP ensures high security for API credentials through encryption and masking. It supports various authentication mechanisms including OAuth, API key, Bearer token, and Basic Auth, with secure credential management.
Source: apitomcp.ai