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    MCP server for AI security scanning. Detects prompt injections, jailbreaks, data exfiltration, and social engineering attacks in real-time using 42 regex patterns via the ClawGuard Shield API. Sub-10ms response times.
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    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.
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    MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.
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    MIT
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    Open behavioral litmus for MCP servers — grades A–F across tool-output injection, egress, sensitive-data, and adversarial-input, with reproducible, content-addressed evidence. Tools: run_litmus, verify_attestation.
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    Apache 2.0
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    A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.
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    Apache 2.0
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    Enables natural language-driven creation and execution of autonomous-vehicle scenarios in the CARLA simulator, with validated primitives and replay support.
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    MIT
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    Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.
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    Enables agents to validate UI designs for missing states, accessibility issues, and journey completeness using state machine modeling.
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    MIT
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    MCP server for AI agents to compile, playtest, and exhaustively explore ink interactive fiction stories, catching compile errors, runtime errors, unreachable content, and verifying story structure.
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    Enables quality checking and content management for websites through the Crownpeak DQM CMS REST API. Supports running quality checks, spellchecking, asset management, and checkpoint monitoring with both desktop and cloud deployment options.
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    MIT
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    Enables interaction with AWS Fault Injection Service to create, manage, and execute chaos engineering experiments. Operates in read-only mode by default for security, with optional write operations for starting/stopping experiments and managing templates.
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    MCP server for managing Apidog test cases, scenarios, suites, and test data, providing full read/write access to Apidog's test management features.
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    Adversarial AI review API — independent AI reviews another AI's output. Stop LLMs from grading their own homework. Provides automated quality assurance for AI-generated code, content, and other outputs through independent review pipelines.
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    MIT