"Headroom open-notebook resources" matching MCP servers:

Provides an in-memory notebook interface with tools to create, retrieve, list, update, and delete notes, designed to test agent behavior through realistic MCP tool interactions.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

Open-source verification for evidence-grounded AI. Runs deterministic grounding checks of AI outputs against source evidence, with no LLM judge.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

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.

Scans any website and produces an Agent Readiness Report scored on the open ASO framework.

An MCP server that gives AI assistants the ability to check open-source packages for vulnerabilities, enrich findings with real-world exploit intelligence, and statically analyse whether vulnerable code is actually reachable in your project.

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.

Checks MCP servers by URL, npm package, or official MCP Registry search, reporting availability, response speed, exposed tools, resources, and prompts. It flags changes since prior runs as breaking, warning, or info using saved snapshots.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

Gives your coding agent the review comments left on a running frontend with Maple. It lists open comments with the element, source location and screenshot they point to, waits for new ones, and resolves them when the fix is in.

Enables AI agents and developers to inject controlled browser network faults—such as API failures, latency, blocked resources, dropped connections, corrupted payloads, and transient errors—and assert whether web apps recover or degrade gracefully.

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.

IFC/BIM toolkit with a free browser 3D viewer: validate IFC with a 0–100 Health Score, check buildingSMART IDS 1.0, read DXF drawings, and open models, floor plans, 3D sketches and live digital twins in 3D. Validation runs locally and files are not uploaded.

Enables building and evaluating shopping/support agents against a deterministic synthetic retail store with in-memory fixtures. Provides tools, resources, and prompts for product search, cart and order flows, inventory, and policy retrieval over stdio or Streamable HTTP.

A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.

Enables AI coding agents to inspect annotated screenshots, user action steps, console errors, and failed network requests from bug reports, with tools, resources, and prompts for diagnosis and triage.

Open-source MCP server and CLI. It maps every function to the tests that call it, ranks untested risk, and uses mutation proof to show a test catches a break. Local, MIT.

Enables coding agents to open the same web page across persistent mobile, tablet, and desktop viewports, interact with it, capture screenshots, inspect the accessible DOM, and run responsive layout audits without losing state between calls.

Small diagnostic MCP server for checking what MCP clients actually support, including tools, resources, prompts, and transport behavior.

Enables designing and analyzing retail-offer experiments, including sample-size planning, hash-based cell assignment, lift estimation with CUPED and bootstrap, sample-ratio checks, and experiment lifecycle management. It also supports drafting readouts and accessing synthetic datasets and experiment resources through MCP clients.

Checks the outcome after an agent handoff, when a request, 200 or ack only shows the handoff. Reads one field of one exact public HTTPS JSON record, with a same-site known-good control, for 20-120 s. Returns PROVED, DISPROVED or INCONCLUSIVE with a signed receipt you can verify. 5 free checks, then USD 1 per completed check, by card (Stripe Checkout) or existing Link wallet. INCONCLUSIVE is free.

Enables evaluating Python projects against a deterministic quality bar using analyzer findings, per-dimension scores, and a review verdict, exposed through MCP tools, resources, and prompts. Users can run evaluations, inspect rules, and list analyzers to assess code readiness for review.

Enables AI assistants to manage Apple App Store Connect resources like apps, builds, TestFlight, and reviews through natural language.

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

Enables AI coding agents to open and exercise web applications in an isolated Chromium browser, capture screenshots and runtime/network diagnostics, and run deterministic page checks with linked evidence.

MCP server for QTM4J (QMetry Test Management for Jira) Open API, enabling test case and cycle management via natural language.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

Enables agents to work with Robot Framework by discovering tests and resources, drafting tests from requirements, dry-running and executing suites, and parsing output.xml results.

A test MCP server that exercises all protocol features including tools, resources, prompts, and sampling to help client builders validate implementations.