MCP server
by matthewhand
OpenAPI enables seamless integration of external services via REST APIs like Jira and Confluence, using OpenAPI specs fo
Dynamically exposes REST APIs defined by OpenAPI specifications as MCP tools, enabling seamless integration of external services into workflows.
OpenAPI is a community-built MCP server published by matthewhand that provides AI assistants with tools and capabilities via the Model Context Protocol. OpenAPI enables seamless integration of external services via REST APIs like Jira and Confluence, using OpenAPI specs fo It is categorized under developer tools.
You can install OpenAPI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
OpenAPI is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
OpenAPI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: OpenAPI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend OpenAPI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
OpenAPI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
OpenAPI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: OpenAPI is the kind of server we cite when onboarding engineers to host + tool permissions.
According to our notes, OpenAPI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
OpenAPI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
OpenAPI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated OpenAPI against two servers with overlapping tools; this profile had the clearer scope statement.
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mcp-openapi-proxy is a Python package that implements a Model Context Protocol (MCP) server, designed to dynamically expose REST APIs—defined by OpenAPI specifications—as MCP tools. This facilitates seamless integration of OpenAPI-described APIs into MCP-based workflows.
The package offers two operational modes:
/chat/completions becomes chat_completions()).list_functions() and call_function()) based on static configurations.Bearer by default for API_KEY in the Authorization header, customizable for APIs like Fly.io requiring Api-Key.Install the package directly from PyPI using the following command:
uvx mcp-openapi-proxy
To incorporate mcp-openapi-proxy into your MCP ecosystem configure it within your mcpServers settings. Below is a generic example:
{
"mcpServers": {
"mcp-openapi-proxy": {
"command": "uvx",
"args": ["mcp-openapi-proxy"],
"env": {
"OPENAPI_SPEC_URL": "${OPENAPI_SPEC_URL}",
"API_KEY": "${API_OPENAPI_KEY}"
}
}
}
}
Refer to the Examples section below for practical configurations tailored to specific APIs.
OPENAPI_SIMPLE_MODE=true.OPENAPI_SPEC_URL: (Required) The URL to the OpenAPI specification JSON file (e.g. https://example.com/spec.json or file:///path/to/local/spec.json).OPENAPI_LOGFILE_PATH: (Optional) Specifies the log file path.OPENAPI_SIMPLE_MODE: (Optional) Set to true to enable FastMCP mode.TOOL_WHITELIST: (Optional) A comma-separated list of endpoint paths to expose as tools.TOOL_NAME_PREFIX: (Optional) A prefix to prepend to all tool names.API_KEY: (Optional) Authentication token for the API sent as Bearer <API_KEY> in the Authorization header by default.API_AUTH_TYPE: (Optional) Overrides the default Bearer Authorization header type (e.g. Api-Key for GetZep).STRIP_PARAM: (Optional) JMESPath expression to strip unwanted parameters (e.g. token for Slack).DEBUG: (Optional) Enables verbose debug logging when set to "true", "1", or "yes".EXTRA_HEADERS: (Optional) Additional HTTP headers in "Header: Value" format (one per line) to attach to outgoing API requests.SERVER_URL_OVERRIDE: (Optional) Overrides the base URL from the OpenAPI specification when set, useful for custom deployments.TOOL_NAME_MAX_LENGTH: (Optional) Truncates tool names to a max length.OPENAPI_SPEC_URL_<hash> – a variant for unique per-test configurations (falls back to OPENAPI_SPEC_URL).IGNORE_SSL_SPEC: (Optional) Set to true to disable SSL certificate verification when fetching the OpenAPI spec.IGNORE_SSL_TOOLS: (Optional) Set to true to disable SSL certificate verification for API requests made by tools.For testing you can run the uvx command as demonstrated in the examples then interact with the MCP server via JSON-RPC messages to list tools and resources. See the "JSON-RPC Testing" section below.
Glama offers the most minimal configuration for mcp-openapi-proxy requiring only the OPENAPI_SPEC_URL environment variable. This simplicity makes it ideal for quick testing.
Retrieve the Glama OpenAPI specification:
curl https://glama.ai/api/mcp/openapi.json
Ensure the response is a valid OpenAPI JSON document.
Add the following configuration to your MCP ecosystem settings:
{
"mcpServers": {
"glama": {
"command": "uvx",
"args": ["mcp-openapi-proxy"],
"env": {
"OPENAPI_SPEC_URL": "https://glama.ai/api/mcp/openapi.json"
}
}
}
}
Start the service with:
OPENAPI_SPEC_URL="https://glama.ai/api/mcp/openapi.json" uvx mcp-openapi-proxy
Then refer to the JSON-RPC Testing section for instructions on listing resources and tools.
Fly.io provides a simple API for managing machines making it an ideal starting point. Obtain an API token from Fly.io documentation.
Retrieve the Fly.io OpenAPI specification:
curl https://raw.githubusercontent.com/abhiaagarwal/peristera/refs/heads/main/fly-machines-gen/fixed_spec.json
Ensure the response is a valid OpenAPI JSON document.
Update your MCP ecosystem configuration:
{
"mcpServers": {
"flyio": {
"command": "uvx",
"args": ["mcp-openapi-proxy"],
"env": {
"OPENAPI_SPEC_URL": "https://raw.githubusercontent.com/abhiaagarwal/peristera/refs/heads/main/fly-machines-gen/fixed_spec.json",
"API_KEY": "<your_flyio_token_here>"
}
}
}
}
<your_flyio_token_here>).Api-Key for Fly.io’s header-based authentication (overrides default Bearer).After starting the service refer to the JSON-RPC Testing section for instructions on listing resources and tools.
Render offers infrastructure hosting that can be managed via an API. The provided configuration file examples/render-claude_desktop_config.json demonstrates how to set up your MCP ecosystem quickly with minimal settings.
Retrieve the Render OpenAPI specification:
curl https://api-docs.render.com/openapi/6140fb3daeae351056086186
Ensure the response is a valid OpenAPI document.
Add the following configuration to your MCP ecosystem settings:
{
"mcpServers": {
"render": {
"command": "uvx",
"args": ["mcp-openapi-proxy"],
"env": {
"OPENAPI_SPEC_URL": "https://api-docs.render.com/openapi/6140fb3daeae351056086186",
"TOOL_WHITELIST": "/services,/maintenance",
"API_KEY": "your_render_token_here"
}
}
}
}
Launch the proxy with your Render configuration:
OPENAPI_SPEC_URL="https://api-docs.render.com/openapi/6140fb3daeae351056086186" TOOL_WHITELIST="/services,/maintenance" API_KEY="your_render_token_here" uvx mcp-openapi-proxy
Then refer to the JSON-RPC Testing section for instructions on listing resources and tools.
Slack’s API showcases stripping unnecessary token payload using JMESPath. Obtain a bot token from Slack API documentation.
Retrieve the Slack OpenAPI specification:
---
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.