OpenAPI MCP

OpenAPI MCP is an open-source framework for exposing any [OpenAPI][1]-documented HTTP APIs as [MCP][2] servers. Built on [Spring AI][3] and designed to run as a [Spring Boot][4] application, it's already running in production, powering [Infobip MCP servers][5].

It's production-tested and ready for you to use in your own projects!

Features

The framework is a bridge from the OpenAPI described APIs to MCP servers. Core functionality is mapping HTTP API operations (paths and HTTP methods) to MCP tools. This includes a setup step that happens upfront to prepare tool metadata which is presented to AI agents and a runtime step that happens when AI agents invoke tools.

Some of the core features include:

• Adapting OpenAPI specification to work with MCP tools. APIs have more flexibility in their inputs, e.g. they accept path and query parameters, while MCP tools expect to receive all inputs as a single JSON object. The framework will detect these cases and wrap / unwrap inputs accordingly.
• OpenAPI specification allows advanced features in request schema definitions, such as discriminators for polymorphic models. This is not allowed in pure JSON schema used by MCP, so the framework has a transformation step in which discriminators are resolved and embedded in a way compatible with JSON schema.
• Mock mode in which MCP server returns examples from the OpenAPI specification instead of making HTTP API calls

[!IMPORTANT] The OpenAPI MCP framework allows you to expose any HTTP API documented with OpenAPI to LLM agents. Since LLMs will process the API responses it is important that you trust the API won't compromise your users' agents with prompt injections. It is equally important to trust the OpenAPI specification, as it is used as a source of meta-data that is directly provided to LLMs. When exposing your own APIs make sure that responses are secure and can't be used to inject untrusted text that might contain prompt injection. When exposing 3rd party APIs make sure the API itself is trusted, but also that the OpenAPI specification which defines it is equally trusted. When working with 3rd party OpenAPI specifications you can review and store them as a static files inside your application resources. That way you can be sure specifications won't change unexpectedly.

Authentication

Authentication and authorization is important for MCP servers, and can be tricky to implement. In case of exposing HTTP APIs as MCP tools the security posture of the API is bases for everything. The OpenAPI MCP framework adapts it to MCP specification in few key ways:

• The framework exposes required /.well-known HTTP endpoints. Two of them (/.well-known/openid-configuration and /.well-known/oauth-authorization-server) are proxied to your [authorization server][5], and one (the /.well-known/oauth-protected-resource) is handled by the framework itself.
• There is the option of supporting authorization checking API endpoint that framework invokes before processing MCP interactions to validate client credentials.

Lastly, by delegating authentication to dedicated API endpoint, the framework supports arbitrary auth type, such as classic API key and Basic auth types, in addition to OAuth.

There are more technical features that enable customizing various behaviors, like:

• OpenAPI filters that can be used to programmatically customize the specification before MCP tool metadata is constructed.
• [OpenAPI extensions][7] that can be used to customize different aspects of MCP tools, including listing custom OAuth scopes.
• Several naming strategies are available to customize MCP tool names.
• API request enrichers that can be used to programmatically customize the API requests that back the tool calls.
• MCP tool call filters that can be used to customize tool call behavior.
• A base of [Spring AI][3] external customization options, which framework builds on top of with its own options. See below for a full list.

Getting Started

Prerequisites

OpenAPI MCP framework requires Java version 21 of newer, and is based on [Spring Boot][4] 4.1.x and [Spring AI][3] 2.0.x.

Installation

You can install it in your Java project with maven:

<dependency>
    <groupId>com.infobip.openapi.mcp</groupId>
    <artifactId>infobip-openapi-mcp-spring-boot-starter</artifactId>
    <version>0.1.17</version>
</dependency>

or gradle:

implementation("com.infobip.openapi.mcp:infobip-openapi-mcp-spring-boot-starter:0.1.17")

Usage

After installation enable one of the [server protocols supported by Spring AI][8] with externalized configuration properties. For example, you can enable [stdio transport][9] with a config like this:

spring:
  ai:
    mcp:
      server:
        type: sync
        stdio: on

[!IMPORTANT] Make sure to set the server type to sync, as some of the framework features (such as authentication) will not work with the async type.

To expose a remote server using the currently recommended [streamable HTTP transport][10] use this config:

spring:
  ai:
    mcp:
      server:
        protocol: STATELESS

Configuration

OpenApiFilter

You can implement and register beans of type com.infobip.openapi.mcp.openapi.filter.OpenApiFilter to change the OpenAPI specification before framework extracts MCP tool meta-data from it. Individual filters can be disabled in externalized configuration with the infobip.openapi.mcp.filters.[filter-name] property. For example, to disable the built-in filter that removes regex pattern property from OpenAPI schemas set infobip.openapi.mcp.filters.PatternPropertyRemover: false.

[!TIP] AI agents perform best with smaller, focused MCP servers. On the contrast, HTTP APIs are ofter large and full of different features. This means we usually need to pick a subset of API operations that will be included as tools. Sometimes we need to also pick a limited subset of input parameters like query parameters or even request body properties. There are two ways to prepare OpenAPI specification for this:

1. You can make a dedicated OpenAPI specification for your MCP servers. This can be done either from scratch, or by transforming the original specification with something like [OpenAPI overlays][12]. This transformation can be automated as part of your CI pipeline. In this case your MCP server will receive the limited-scope specification with only the elements that you selected to expose to AI agents.
2. Alternatively, you can provide MCP server with the original, fully featured specification and narrow down its scope by implementing OpenAPI filters in your application code.

Both approaches can be combined.

Parameter handling

OpenAPI allows parameters to be serialized in different [styles][19], with or without explode. The framework currently only supports the OpenAPI default: form style with explode: true for query and cookie parameters, and simple style with explode: false for header parameters. Given a parameter named color:

Note that a query or cookie object value is exploded into one parameter per property, named after the property rather than color, matching the OpenAPI specification for form style with explode: true. A header object value instead keeps the single color header name and lists each property name and value as comma-separated pairs, matching simple style with explode: false. The specification leaves object serialization undefined for form style cookies with explode: true; the framework mirrors query parameter handling for consistency, but this is not a spec-mandated behavior. Other styles and explode combinations are not currently supported.

Tool NamingStrategy

MCP servers expose functionalities to AI agents as tools. Each tool is identified by a name which is accompanied by a description. LLMs pick tools to use based on this information, so it is important to make them concise and clear. The framework implements several strategies for naming tools:

1. OperationIdStrategy, which produces names based on operationId from OpenAPI specification.
2. SanitizedOperationIdStrategy which uses operationId, but sanitizes it by lowercasing alphanumeric characters and replacing others with underscore.
3. EndpointStrategy, which combines HTTP method and path.

Various MCP client libraries have different limitations on the maximum tool name length. To accommodate this the framework provides TrimNamingStrategy, which wraps one of the base strategies and enforces length limits on top of it.

You can customize tool naming with infobip.openapi.mcp.tools.naming.strategy and infobip.openapi.mcp.tools.naming.max-length external configuration properties. If provided implementations do not meet your needs you can provide your own implementation.

[!TIP] Many MCP client libraries implement scoping of tool names. Common pattern is to allow client applications to name each MCP server they connect to, and to prepend the server name to names of tools loaded from the server. This means you as MCP server developer do not need to scope your tool names. It is best to keep names short and to the point.

Tool descriptions

LLMs pick tools based on their names and descriptions. In order for them to be able to do that descriptions of all tools from all MCP servers that an agent is connected to are loaded into LLM context. This means that tool descriptions need to be as short as possible while retaining clarity, but not shorter than that.

The OpenAPI MCP framework can use few API operation properties to create tool descriptions. It can either take just the operation summary, or it can combine it with operation description. The behavior can be controlled with infobip.openapi.mcp.tools.prepend-summary-to-description externalized configuration property.

The framework can also append a request example to each tool description as a Markdown JSON code block. Examples are extracted from the OpenAPI specification — from parameters and request bodies — and combined into a single object mirroring the tool's input schema structure. The behavior is controlled by the infobip.openapi.mcp.tools.examples-mode property, which accepts three values:

• SKIP (default) — no examples are appended.

• ALL — all examples from the OpenAPI specification are included.

• ANNOTATED — only examples explicitly marked for MCP use are included. Mark an example by adding x-mcp-example: true directly on the OpenAPI Example Object (inside the examples map of a parameter or request body):

  examples:
    basicRequest:
      summary: Basic SMS
      x-mcp-example: true
      value:
        to: "41793026727"
        text: "Hello"
    advancedRequest:
      summary: Advanced SMS (not shown in MCP)
      value:
        to: "41793026727"
        text: "Hello"
        validityPeriod: 720
  

[!TIP] Be mindful that examples add to the context size consumed by tool descriptions. If the examples in your OpenAPI specification are large or numerous, ANNOTATED mode is the recommended approach — it lets you selectively expose only the examples that are most useful for the LLM, without needing OpenAPI overlays or custom filters.

Tool annotations

MCP tools support [annotations][15] that describe their behavior to MCP clients. The framework automatically infers annotations from the HTTP method of each API operation:

openWorldHint is always true because every tool calls an external HTTP API.

Annotations can be overridden per-operation using the x-mcp-annotations [vendor extension][7] on the OpenAPI Operation object:

paths:
  /messages:
    post:
      operationId: sendMessage
      x-mcp-annotations:
        idempotentHint: true

They can also be overridden globally per tool name using externalized configuration properties:

infobip:
  openapi:
    mcp:
      tools:
        annotations:
          sendMessage:
            idempotent-hint: true

Override precedence (lowest to highest): HTTP method defaults, x-mcp-annotations vendor extension, YAML configuration properties. Each layer only overrides fields it explicitly sets; unset fields fall through from the previous layer.

Authentication

MCP defines OAuth as preferred authentication method. The framework aims to make this as easy to implement as possible. There are few considerations when exposing existing APIs:

1. The underlying API must implement the same authentication type as MCP server.
2. There are few specifics of MCP specification that need to be satisfied for clients to work automatically.

One of MCP requirements is that first interaction with MCP server that doesn't include valid credentials should be rejected; in fact that is what triggers the login flow in MCP clients. However, this interaction is usually not direct tool invocation, meaning that the framework does not need to make any API calls to implement tool calls. Since credentials still need to be verified framework needs to invoke some API endpoint which only performs the authentication. This special endpoint, which is not exposed as a tool but is used only in this auth flow, needs to be defined in an externalized configuration property infobip.openapi.mcp.security.auth.auth-url. This is needed whenever security is enabled. The framework will pass any Authorization header from the inbound MCP request to the auth-url endpoint on the API.

OAuth

MCP specification defines a flow for automatic [authorization server discovery][13]. One of the requirements is that MCP server itself should expose few /.well-known HTTP endpoints defined by the OAuth specification. Some of these are usually implemented by the OAuth authorization server, and the OpenAPI MCP framework can proxy those calls to make it more convenient to expose them from the same server as the rest of MCP features. Some endpoints are implemented and exposed directly by the framework, as in acts as OAuth resource server.

OAuth APIs usually rely on scopes for fine-grained access control, and MCP specification allows for this. OpenAPI MCP framework takes the OAUth scope information from the provided OpenAPI specification. The framework looks for scopes either in standard security properties or in custom operation-level OpenAPI extensions that can be defined in infobip.openapi.mcp.security.auth.oauth.scope-discovery.scope-extensions. Additionally, fixed, predefined scopes can also be defined with infobip.openapi.mcp.security.auth.oauth.scope-discovery.mandatory-scopes.

You can configure what set from all discovered scopes are requested during login by setting the externalized configuration property infobip.openapi.mcp.security.auth.oauth.scope-discovery.calculate-minimal-scopes. When NONE is used, which is the default, all discovered scopes are requested. When GREEDY is used an optimistic greedy algorithm picks a subset of scopes which still covers all operations.

ApiRequestEnricher

If you need to customize HTTP requests that the framework is making towards the API you can implement and register beans of type com.infobip.openapi.mcp.enricher.ApiRequestEnricher. This is a good place to include any meta-data for monitoring or custom tracing that you may need. Framework provides few enrichers out of the box, for example the one that sets the User-Agent header to the value defined in externalized configuration property infobip.openapi.mcp.user-agent.

[!NOTE] Implementations of API request enrichers should be lightweight and non-critical. The framework will skip enrichers that fail by catching any exceptions and carry on to make the API request. This is why the enricher interface is limited to tweaking Spring's RestClient.RequestHeadersSpec and does not provide options to break the flow and prevent the API call from being made.

CredentialProvider

The framework uses com.infobip.openapi.mcp.auth.CredentialProvider to obtain the credential value used for authenticating incoming requests and forwarding authorization to the downstream API. The default implementation reads the Authorization header from the incoming HTTP request.

You can replace this bean to supply credentials from any source:

@Bean
public CredentialProvider credentialProvider() {
    return context -> Optional.of(myVaultClient.getApiKey())
            .filter(key -> !key.isBlank())
            .map(key -> "Bearer " + key);
}

[!NOTE] If the provider throws an unchecked exception, the framework catches it and fails closed: InitialAuthenticationFilter returns HTTP 401, and ToolHandler returns an error tool result with an authentication error.

ToolCallFilter

You can implement and register beans of type com.infobip.openapi.mcp.openapi.tool.ToolCallFilter to customize the tool call handling behavior. Tool call filters can modify requests before making API calls, as well as API responses before returning them to MCP client. They are also a good place to implement custom observability. Unlike API request enrichers, tool call filters can break the processing chain, thus preventing the API call from being made.

The com.infobip.openapi.mcp.openapi.tool.RegisteredTool provides the default implementation of a tool filter which makes the HTTP API call. It is registered with the lowest precedence, so you can preempt it by using any precedence higher than that.

PromptCallFilter

You can implement and register beans of type com.infobip.openapi.mcp.prompt.PromptCallFilter to customize prompt call handling behavior. Prompt call filters can inspect or modify prompt requests before resolution, inspect or modify prompt results before returning them to the MCP client, and short-circuit the chain to prevent prompt resolution entirely. They are a good place to implement custom observability, authorization, or caching for prompt calls.

The com.infobip.openapi.mcp.prompt.RegisteredPrompt provides the default implementation of a prompt filter which performs the actual prompt resolution (inline template rendering or backend HTTP call). It is registered with the lowest precedence, so you can preempt it by using any precedence higher than that.

JSON serialization

Both MCP client libraries and underlying LLMs can sometimes produce invalid JSON documents and send them to MCP server tools. The OpenAPI MCP framework implements a helper to address one of the common errors: embedding JSON sub-objects into strings. This is a common failure mode in which a sub-object property of a complex request model is sent to MCP server inside a JSON string. The framework will first send this request to HTTP API as normal, but will likely receive a HTTP status code 400 response. In that case framework will attempt to unwrap string property values and look for a JSON object or a JSON array inside it. If it detects such a case, it sends another HTTP API requests with the corrected request body.

You can disable this behavior by setting externalized configuration property infobip.openapi.mcp.tools.json-double-serialization-mitigation: false.

Mock mode

Framework offers a mock mode in which MCP server will return tool call results based on examples from the OpenAPI specification. Framework picks first example for the successful (2xx range) response with application/json content type from the API endpoint that corresponds to the tool being called. In case example is missing for the specific API endpoint an error MCP result is returned. This feature is disabled by default, and can be enabled by setting the externalized configuration property infobip.openapi.mcp.tools.mock: true.

[!NOTE] Even with mock mode enabled, security features still work and will delegate authentication checks to the server defined by the infobip.openapi.mcp.security.auth.auth-url property. This allows MCP client implementors to test authentication configuration on their end, including OAuth config.

If this is not desired you can disable authentication by setting infobip.openapi.mcp.security.auth.enabled: false. By disabling auth and enabling mock mode framework won't use API, and all tool calls will receive successful results based on OpenAPI examples.

Tool Reload

The framework supports automatic reloading of the OpenAPI specification at runtime. When enabled, the framework periodically fetches the OpenAPI specification and updates the registered MCP tools if changes are detected. This is useful for scenarios where the OpenAPI specification is updated frequently and you want the MCP server to reflect these changes without requiring a restart.

Tool reload works by comparing the OpenAPI specification version. When a version change is detected, the framework compares the registered tools with the new specification and:

• Removes tools that no longer exist in the specification
• Adds new tools that were introduced in the specification
• Updates tools that have changed (title, description, or schema)
• Discovers new OAuth scopes if scope discovery is enabled

After detecting changes, connected MCP clients are notified about the tool list changes, and OAuth scopes are rediscovered automatically if scope discovery is enabled.

[!NOTE] Due to MCP SDK constraints, notifications are sent after each individual tool modification rather than in batch.

The framework retries up to max-retries times per scheduled execution, but terminates early on the first successful reload (whether or not tools changed). Retries only occur when the reload fails (e.g., due to network errors), using exponential backoff between attempts. If a refresh is already in progress when the next scheduled execution triggers, that execution is skipped.

Prerequisites:

• Add @EnableScheduling to your Spring Boot application configuration

Configuration example:

infobip:
  openapi:
    mcp:
      live-reload:
        enabled: true
        cron-expression: "0 */5 * * * *"  # Every 5 minutes
        max-retries: 3

[!WARNING] The tool reload task runs on Spring's task scheduler thread pool and blocks the thread during execution. By default, Spring uses a single-threaded scheduler. If your application has multiple scheduled tasks and the reload operation takes time (e.g., due to network latency), consider configuring a larger thread pool:

spring:
  task:
    scheduling:
      pool:
        size: 2

Progress Notifications

While an HTTP API call is in progress, the framework can send periodic [notifications/progress][16] messages to MCP clients. This keeps clients responsive during slow API calls and prevents them from timing out prematurely.

[!NOTE] Progress notifications only work with stateful MCP servers (SSE or stateful Streamable HTTP), and only when the MCP client requests them by including _meta.progressToken in the tool call.

The feature is enabled by default. To opt out:

infobip:
  openapi:
    mcp:
      progress-notifications-enabled: false

The interval between notifications defaults to 1 second and can be adjusted with infobip.openapi.mcp.progress-notifications-interval. Keep this value below your read-timeout, otherwise no notification will be sent before the HTTP call completes.

By default, notifications carry an incrementing counter with no total or human-readable message. To customize the progress, total, and message fields, implement ProgressUpdateProvider and register it as a Spring bean:

@Bean
public ProgressUpdateProvider progressUpdateProvider() {
    return new ProgressUpdateProvider() {
        @Override
        public Double total(McpRequestContext context) {
            return null; // unknown duration
        }

        @Override
        public ProgressUpdate next(long tick, McpRequestContext context) {
            var toolName = context.toolName() != null ? context.toolName() : "tool";
            return new ProgressUpdate(tick, "Waiting for " + toolName + "…");
        }
    };
}

The total value is resolved once before the first notification and stays constant throughout the tool call, so clients that display a progress fraction always receive a consistent value.

Prompts

The framework supports [MCP prompts][17] — reusable prompt templates that MCP clients can discover and invoke. Prompts are defined using the x-mcp-prompts [vendor extension][7] on the root OpenAPI object as an array of prompt definitions. Two resolution modes are available:

• Static templates — prompts with inline messages containing [Mustache][18] {{placeholder}} templates. Templates are rendered server-side from the user-supplied arguments with no backend call. Missing required arguments fail the request; missing optional arguments render as empty strings.
• Backend resolution — prompts with a resolve block that delegates to a backend HTTP endpoint at runtime. Arguments are forwarded as query parameters for GET or as a JSON request body for POST. Credentials are forwarded using the configured CredentialProvider.

Each prompt must use exactly one mode — defining both messages and resolve on the same prompt causes a startup error.

# Top-level OpenAPI vendor extension (sibling to info, paths, components)
x-mcp-prompts:
  - name: greet
    description: "Greet a user by name"
    arguments:
      - name: user_name
        description: "User's name"
        required: true
    messages:
      - role: user
        content: "Hello {{user_name}}, welcome!"
      - role: assistant
        content: "Thanks! Glad to be here, {{user_name}}."

  - name: summarize
    description: "Summarize the API capabilities"
    arguments:
      - name: format
        description: "Output format (markdown, plain, json)"
    resolve:
      path: /prompts/summarize
      method: POST

The path in the resolve block is resolved relative to the same base URL used for API tool calls (derived from the servers entry in the OpenAPI specification).

For backend-resolved prompts, the endpoint must return a JSON response with the following structure:

{
  "description": "Greet a user",
  "messages": [
    {"role": "user", "content": "Generate a greeting for Alice."},
    {"role": "assistant", "content": "Hello Alice, welcome!"}
  ]
}

Messages support both user and assistant roles, enabling few-shot prompt patterns. Prompts are automatically included in live reload — when the OpenAPI specification changes, prompt additions and removals are detected and connected MCP clients are notified.

Properties

[External configuration properties][11] that can be used to configure framework behavior: