"Mockzila, a tool for creating mock APIs or mock services" matching MCP servers:

Generates schema-compliant mock data from OpenAPI JSON Schema definitions using AI, enabling seamless testing without manual fixtures.

Spin up deterministic mock MCP servers from JSON fixture files for testing MCP clients and agents.

A mock MCP server for testing MCP client implementations and development workflows. Supports tools, prompts, and resources across multiple transport protocols (stdio, HTTP, SSE).

A zero-dependency mock MCP server for testing MCP clients and harnesses, with configurable tools and canned responses.

Enables instant creation of mock API servers from OpenAPI specs or natural language descriptions, with built-in fake data generation, CRUD endpoints, and configurable delays/errors for testing.

Enables developers to run spec-driven, deterministic mock tool interactions for agent integration testing and CI, including fixture-based JSON-RPC responses, call assertions, and error injection without live backends or network access.

A test MCP server that validates gateway connectivity, identity propagation, and provides mock tools for testing purposes.

MCP server to mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations without real API keys or token spend.

Mock Server AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables config-driven mocking of MCP servers for AI skill evaluation, dynamically registering tools from a schema and returning configurable static, fixture-based, or LLM-generated responses.

A lightweight mock MCP server for local testing and resilience experiments, providing predictable tool responses with simulated latency and errors.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

A zero-code-intrusion mock server for mobile apps that integrates with Charles proxy, allowing dynamic rule management via natural language in Cursor.

Enables developers and AI agents to start stateful local twins of real APIs from built-in packs, OpenAPI specs, HAR recordings, or documentation, then inspect requests, state, and webhooks; force scenarios, chaos, and time changes; and reset or stop twins through MCP tools.

A FastAPI + FastMCP dashboard for registering MCP mock server contracts and connecting to them via Streamable HTTP endpoints.

Provides a minimal MCP server that exposes a tool for retrieving lists of tickets, each with a detailed 2,048-byte description field via Streamable HTTP.

Enables AI assistants to interact with a self-hosted Jira clone for testing, supporting project and issue management, comments, and search via MCP tools.

A thin MCP server that wraps provenance-receipts and quality-gate services as tools, enabling AI agents to certify content origin and score quality via Ed25519-signed receipts.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A lightweight MCP server that simulates financial data interactions with dummy authentication and static JSON datasets for testing financial applications.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Enables code execution in 70+ programming languages and databases through the Onecompiler API, allowing users to run and test code directly from their MCP-enabled applications.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

This MCP server verifies that an agent’s claimed tool output matches the actual response returned by a tool to prevent invented or distorted results. It flags mismatches, omissions, and invented fields to ensure downstream logic only processes verified tool data.

Enables verification of deployment-scoped model-visible DSH tool surface conformance by checking recorded tool identities and schemas against approved locks, reporting only drift categories and hashes.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.

A throwaway HTTP MCP server that empirically tests whether Cursor invokes tools by exact name or munges them, to inform case normalization decisions.

A lightweight multi-provider MCP testing fixture with two providers (eva_air and uk_railway), each exposing 5 tools using in-memory fake data, designed for verifying MCP client tool discovery, tool calls, and multi-provider routing.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.