"Coding in Python and R" matching MCP servers:

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

MCP server for reading, writing, and organizing API documentation in Apidog.

A read-only API change deploy gate for AI coding agents that analyzes OpenAPI specs to determine if changes are safe to deploy. It provides tools for comparing specs, explaining breaking changes, and generating migration guides.

MCP server for Mockzilla. Lets coding agents like Claude Code, Claude Desktop, Cursor and Gemini CLI install the Mockzilla CLI and run API mocks from an OpenAPI spec or a single endpoint. Log in from the agent to deploy hosted mocks on mockzilla.org

Enables AI coding assistants to work correctly against Vertafore ImageRight APIs with version-aware configuration and planned API exploration tools.

Python MCP server for running and inspecting Bruno API collections

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.

An MCP server that gives AI coding agents real-time access to the public-apis dataset, enabling search, live probing, and code snippet generation for 1,500+ free public APIs.

Enables AI coding agents to create webhook bins, inspect and replay HTTP requests, and stand up mock API endpoints directly from the editor.

Enables LLMs to dereference and query OpenAPI/Swagger specifications, search endpoints and schemas, validate payloads, extract security schemes, and generate production-ready integration code in multiple languages.

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

Exposes Specmatic's API contract testing, resiliency testing, and mocking capabilities to AI coding agents via natural language, enabling automated validation and simulation of API behaviors.

Enables AI coding assistants to discover, inspect, and run API requests in Bruno collections locally, keeping all data private.

Conformance test harness for Model Context Protocol servers, validating JSON-RPC, transport, capability, schema, and more across multiple spec versions.

A lightweight MCP server that lets coding agents manage a local or remote WireMock instance through the WireMock Admin API, providing tools for creating, updating, deleting, and inspecting mock mappings and request journal entries.

Enables direct integration with YApi API documentation platform in MCP-compatible editors like Cursor, allowing users to query API details, list interfaces, and search endpoints by simply pasting YApi URLs.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

A server that implements the Model Context Protocol (MCP) standard, enabling LLMs like Claude to interact with selected Postman API requests through generated JavaScript tools.