"Target" matching MCP servers:

A stdio MCP server that audits other MCP servers over the live protocol. It connects to any MCP target (stdio or HTTP), lints every tool's schema for agent-usability, then actually calls the tools with deliberately broken inputs to see how the server handles them, and returns a 0–100 conformance score with a per-dimension breakdown rendered as Markdown.

MCP server for fenestra, a pure-Rust native GUI framework. Renders and verifies native UIs headlessly (no display, no GPU): a typed accessibility tree, semantic query/interact, contrast/focus-order/hit-target checks, screenshot diffing, and motion filmstrips.

Evidence-driven quality testing for Model Context Protocol servers. It connects as a real client, captures the complete model-facing contract, identifies agent-usability risks, measures context cost, and executes only explicitly approved target calls.

A minimal MCP server built with the official Python SDK that runs over stdio and exposes a health capability, providing a practical integration-testing target for AI and agent codebases.

Let AI agents inspect and drive running WPF (.NET desktop) apps: visual tree, dependency properties, data bindings and binding errors, DataContext, screenshots (popups included), plus click, select-item, text input, keyboard shortcuts, live property editing and wait-for — via runtime injection, with no changes to the target app.

Audits local datasets and ML training code for target, temporal, and entity leakage, PII exposure, and invalid evaluation design, returning structured evidence and pass/review/block verdicts before model training.

Enables AI agents to drive native 1C TestClient QA automation over stdio or authenticated streamable-HTTP transports, running BDD/Gherkin scenarios, reading and verifying managed forms, and performing target-bound lifecycle and UI operations. It also supports JUnit/Allure reporting and an optional authenticated Windows host bridge for desktop input and screenshots.

Enables comparison of mobile app screenshots against design mockups, with Calorix as the first integration target.

Drives test coverage toward target thresholds by coordinating workspace test execution with code-tree-mcp uncovered-symbol analysis.

Visual frontend accessibility inspector MCP server. WCAG contrast checking, touch target validation, heading hierarchy audits, responsive screenshots, and S+ grading across mobile and desktop viewports.

Enables AI assistants to query, create, and manage Targetprocess entities like user stories, bugs, tasks, and features through natural language and structured tools.

A development tool that serves as a bridge to launch and inspect other stdio MCP servers on demand, ensuring a clean process for every operation. It enables developers to bypass host caching issues by providing tools to list and call target server components during active development.

Turns a build or audit target into a graph of claims that a coding agent must decompose and verify bottom-up against evidence, with judgments pinned to git commits and file hashes and findings recorded as issues on the claims they refute. It keeps an append-only, replayable record of every operation, exposes the standing and frontier of the work, and flags stale judgments when cited code changes.

Enables ChatGPT to initiate a visible, evidence-backed UI/UX audit by returning an exact workspace URL through a read-only start_audit endpoint, where page-scoped Site Tools can measure and judge the target without claiming capture.

Enables an agent to evaluate a target MCP server and verify attestations about it from inside the editor, using read-only, allowlisted tools that never send credentials.

A local observation-only MCP server for macOS that provides secure, atomic evidence capture with strict target approval and manifest-based output.

Writes German business letters and emails (DIN 5008) from Markdown: typesets letters to PDF/A via Typst and measures every finished PDF against target dimensions, so a misplaced fold mark fails instead of being printed. Runs locally over stdio; no network access while rendering.

Provides deterministic, offline, sourced resolutions for 44 mobile game development problems spanning performance, memory, rendering, store policies, IAP billing, crash vitals, live-ops emergencies, and store-policy deadlines, along with pre-launch checklists and launch-day runbooks. It also statically audits project directories for Google Play and App Store compliance, including target SDK, 16 KB ELF alignment, privacy manifests, and secret-file exposure, without any network calls or shell execution.

Enables AI agents to run file-level and project-wide diagnostics for Minecraft datapacks, including syntax, mcdoc/NBT schemas, symbol references, AST and cross-reference analysis. It also supports checking server readiness, target Minecraft version, workspace information, and restarting the LSP process.

Enables agents to diagnose JSON incompatibilities against target schemas and explicit rules, then receive bounded deterministic repairs independently verified before delivery.