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Swagger MCP Server

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Swagger MCP Server

A Model Context Protocol (MCP) server that provides tools for exploring and testing APIs through Swagger/OpenAPI documentation. This server automatically detects configuration files from multiple IDEs and provides comprehensive API interaction capabilities.

Features

  • 🔍 Fetch and parse Swagger/OpenAPI documentation from any URL

  • 🧪 Test API endpoints directly through the MCP interface

  • 📊 Explore API schemas and understand data structures

  • 🔧 Multi-IDE support - automatically detects config from VS Code, Cursor, Windsurf, and more

  • 🌐 Flexible authentication - supports API keys, basic auth, and bearer tokens

  • ⚡ Auto-discovery - can find documentation URLs automatically

Related MCP server: MCP-QA

Configuration

IDE Setup

Create an MCP configuration file in your IDE's configuration directory:

  • VS Code: ~/.vscode/mcp.json or .vscode/mcp.json (in your project)

  • Cursor: ~/.cursor/mcp.json or .cursor/mcp.json (in your project)

  • Windsurf: ~/.windsurf/mcp.json or .windsurf/mcp.json (in your project)

  • Any IDE: mcp.json (in your project root) or .mcp/config.json

Authentication Options

Option 1: Using API Key

"swagger-mcp": {
  "command": "npx",
  "args": [
    "-y",
    "swagger-mcp@latest"
  ],
  "env": {
    "API_BASE_URL": "https://api.example.com",
    "API_DOCS_URL": "https://api.example.com/swagger.json",
    "API_KEY": "your-api-key-here"
  }
}

Option 2: Using Username and Password

"swagger-mcp": {
  "command": "npx",
  "args": [
    "-y", 
    "swagger-mcp@latest"
  ],
  "env": {
    "API_BASE_URL": "https://api.example.com",
    "API_DOCS_URL": "https://api.example.com/swagger.json",
    "API_USERNAME": "your-username",
    "API_PASSWORD": "your-password"
  }
}

Configuration Options

  • API_BASE_URL - Base URL for your API (e.g., https://api.example.com) [Required]

  • API_DOCS_URL - Direct URL to Swagger/OpenAPI JSON/YAML (optional, will be auto-discovered)

  • API_KEY - API key for authentication (used as Bearer token)

  • API_USERNAME - Username for basic authentication

  • API_PASSWORD - Password for basic authentication

Authentication Flow

The server intelligently handles authentication:

  1. For API requests: Uses API_KEY as Bearer token, falls back to Basic auth

  2. For authentication endpoints: Auto-injects username/password credentials

  3. Token management: Automatically stores and reuses tokens from login responses

  4. Auto-refresh: Attempts to refresh tokens on 401 Unauthorized responses

Available Tools

fetch_swagger_info

Fetches and parses Swagger/OpenAPI documentation from a given URL to discover available API endpoints.

list_endpoints

Lists all available API endpoints after fetching Swagger documentation, showing methods, paths, and summaries.

get_endpoint_details

Gets detailed information about a specific API endpoint including parameters, request/response schemas, and examples.

execute_api_request

Executes an API request to a specific endpoint with authentication, parameters, headers, and body handling.

validate_api_response

Validates an API response against the schema definitions from Swagger documentation to ensure compliance.

Usage Examples

Once configured, you can use the MCP server in your AI-powered editor to:

  • Explore APIs: "Show me the available endpoints in this API"

  • Test endpoints: "Test the POST /users endpoint with this data"

  • Understand schemas: "Explain the User model structure"

  • Debug API calls: "Help me troubleshoot this API request"

  • Validate responses: "Check if this response matches the API schema"

Supported IDEs

The server automatically detects configuration files from:

  • VS Code (.vscode/mcp.json)

  • Cursor (.cursor/mcp.json)

  • Windsurf (.windsurf/mcp.json)

  • Root directory (mcp.json)

  • Alternative location (.mcp/config.json)

Development

# Clone the repository
git clone https://github.com/amrsa1/SwaggerMCP.git
cd SwaggerMCP

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Available Tools

5 tools
execute_api_requestC

Execute an API request to a specific endpoint

ParametersJSON Schema
NameRequiredDescriptionDefault
methodYesHTTP method (GET, POST, PUT, DELETE, etc.)
pathYesThe endpoint path (e.g., '/users/123')
paramsNoQuery parameters as key-value pairs
bodyNoRequest body as a JSON object (for POST/PUT/PATCH)
headersNoCustom headers as key-value pairs

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool executes an API request but fails to describe critical traits such as authentication requirements, error handling, rate limits, side effects (e.g., whether it modifies data), or response format. This leaves significant gaps for a tool that could perform destructive operations like DELETE.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a general-purpose tool, though it could be more front-loaded with key details if it were more comprehensive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of executing arbitrary API requests (with potential for mutations, auth needs, etc.), no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects, return values, or usage context, making it inadequate for safe and effective tool selection by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all 5 parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't clarify parameter interactions or provide examples), resulting in a baseline score of 3 where the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action ('execute') and resource ('API request to a specific endpoint'), which provides a basic purpose. However, it lacks specificity about what kind of API or system this targets, and it doesn't clearly differentiate from sibling tools like 'fetch_swagger_info' or 'validate_api_response', which might involve similar API interactions but for different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., for testing or production calls), or exclusions, leaving the agent to infer usage based on the generic name and parameters alone, which is insufficient given the presence of sibling tools like 'get_endpoint_details' or 'list_endpoints'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_swagger_infoC

Fetch Swagger/OpenAPI documentation to discover available API endpoints

ParametersJSON Schema
NameRequiredDescriptionDefault
urlNoURL to the swagger.json or swagger.yaml file. If not provided, will try to use the base URL with common Swagger paths.

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves—such as whether it makes network requests, handles errors, returns structured data, or has any side effects. This leaves significant gaps for an agent to understand the tool's operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex API documentation. It doesn't explain what the output looks like (e.g., JSON/YAML structure), potential errors, or how it interacts with sibling tools, leaving the agent with insufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the schema already documents the single parameter ('url') adequately. The description adds no additional meaning or context about the parameter beyond what's in the schema, such as examples or constraints, but this is acceptable given the high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('fetch') and resource ('Swagger/OpenAPI documentation'), and indicates what it's used for ('to discover available API endpoints'). However, it doesn't explicitly differentiate this from sibling tools like 'list_endpoints' or 'get_endpoint_details', which might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'list_endpoints' or 'get_endpoint_details'. It mentions the purpose but doesn't specify scenarios, prerequisites, or exclusions that would help an agent choose between these related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_endpoint_detailsB

Get detailed information about a specific API endpoint

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesThe endpoint path to get details for (e.g., '/users/{id}')
methodYesThe HTTP method (GET, POST, PUT, DELETE, etc.)

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information, implying a read-only operation, but doesn't specify aspects like authentication requirements, rate limits, error handling, or the format of the returned details. This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part earns its place by directly stating the tool's function, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It clarifies the purpose but lacks behavioral details and usage guidelines. Without an output schema, it doesn't explain return values, which could be a gap, but the description focuses on the input aspect, making it borderline complete for a basic read operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with clear descriptions for both parameters ('path' and 'method'), so the schema does the heavy lifting. The description adds no additional parameter semantics beyond implying that these inputs identify a 'specific API endpoint', which is already inferred from the schema. Baseline 3 is appropriate as the schema provides adequate documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('detailed information about a specific API endpoint'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'fetch_swagger_info' or 'list_endpoints', which likely provide similar API information but with different scopes or formats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'fetch_swagger_info' (which might retrieve broader API documentation) and 'list_endpoints' (which might list endpoints without details), the description lacks context for selection, leaving the agent to infer usage based on tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_endpointsB

List all available API endpoints after fetching Swagger documentation

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that endpoints are listed 'after fetching Swagger documentation', hinting at a dependency or sequence, but it doesn't describe what 'list' entails (e.g., format, pagination, or if it's a read-only operation). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core action ('List all available API endpoints') and adds necessary context ('after fetching Swagger documentation'). There is no wasted verbiage, and every part of the sentence contributes to understanding the tool's purpose and sequence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity is low (0 parameters, no output schema), the description is adequate but has gaps. It covers the purpose and hints at a sequence, but without annotations or output schema, it lacks details on behavior (e.g., what 'list' returns, any side effects). For a simple listing tool, it's minimally viable but could be more complete by clarifying the output or dependencies.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it appropriately doesn't mention any. Baseline is 4 for 0 parameters, as the description doesn't introduce confusion or redundancy.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all available API endpoints') and the resource ('API endpoints'), making the purpose immediately understandable. It distinguishes itself from siblings like 'fetch_swagger_info' by specifying it operates 'after fetching Swagger documentation', though it doesn't explicitly contrast with all siblings like 'get_endpoint_details'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning 'after fetching Swagger documentation', suggesting a prerequisite or sequence, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_endpoint_details' or 'execute_api_request'. No exclusions or clear alternatives are stated, leaving usage context somewhat vague.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

validate_api_responseB

Validate an API response against the schema from Swagger documentation

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesThe endpoint path
methodYesThe HTTP method
statusCodeYesThe HTTP status code
responseBodyYesThe response body to validate

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool validates responses but doesn't explain how validation works (e.g., returns validation errors, success/failure status), what happens on failure, or any side effects. For a validation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, validation logic) and lack of annotations or output schema, the description is minimally adequate. It covers the basic purpose but fails to provide critical context like validation outcomes, error handling, or integration with sibling tools, leaving gaps for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, clearly documenting all four parameters (path, method, statusCode, responseBody). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Validate an API response against the schema from Swagger documentation'. It specifies the verb 'validate' and the resource 'API response', making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'execute_api_request' or 'fetch_swagger_info', which might handle related but distinct operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing Swagger documentation loaded), context (e.g., after an API call), or exclusions. With siblings like 'execute_api_request' and 'fetch_swagger_info', this lack of differentiation leaves usage ambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 5 tool updates
    • First observedexecute_api_request
    • First observedfetch_swagger_info
    • First observedget_endpoint_details
    • First observedlist_endpoints
    • First observedvalidate_api_response
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.6/5.0

Scored across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: fetching documentation, listing endpoints, getting endpoint details, executing requests, and validating responses. The descriptions make it easy to tell them apart, and there is no ambiguity in their functions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., execute_api_request, fetch_swagger_info). The naming is uniform and predictable, using snake_case throughout without any deviations or mixed conventions.

Tool Count5/5

With 5 tools, the server is well-scoped for its purpose of interacting with Swagger/OpenAPI documentation and executing API requests. Each tool serves a specific role in the workflow, and the count is neither too sparse nor excessive for the domain.

Completeness5/5

The tool set provides complete coverage for the Swagger/OpenAPI domain: it supports fetching documentation, discovering endpoints, getting details, executing requests, and validating responses. There are no obvious gaps, and agents can perform a full lifecycle from discovery to execution and validation.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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