"Optimizing AI Model Thinking, Token Usage, and Context Size" matching MCP servers:

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.

A simple MCP server that can enable MCP clients to query Bluesky instances.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

An MCP server for validating JSON against schemas, checking email deliverability, verifying URLs, assessing data quality, and validating API responses using RFC-compliant checks and heuristic analysis.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

Webhook management and debugging. Validate signatures, log events, replay, and analyze webhook traffic.

Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.

API Tester AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.

Schema Validator AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables MCP-compatible clients to execute Playwright-based UI and API test suites (login, inventory, checkout, API, regression) and receive structured JSON test results.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

This server acts as a Message Communication Protocol (MCP) service for integrating Apifox and Cursor, enabling OpenAPI interface implementation through AI-driven interaction.

Provides OpenAPI validation and analysis tools to assist developers in building Model Context Protocol servers. It generates developer context and specific agent prompts based on API specifications to streamline the creation of agentic workflows.

One workspace for every AI coding assistant. Governance tools for API lint, diff, persistent ledger, multi-model deliberation, security audit, and test verification. Works with Claude Code, Codex, Cursor, and Gemini CLI.

A standalone Model Context Protocol server that enables AI models to access the Australian Pharmaceutical Benefits Scheme (PBS) API data, including medicine listings, pricing, and availability information.