"Archive of Our Own" matching MCP servers:

Free MCP tools for context engineering audits of AI agents, offering on-demand analysis of system prompts, tool definitions, and context packing.

Read-only MCP server that exposes the agentic-os governance, SDLC, and Quality Engineering methodology to any MCP host. It never writes to your repository and never executes code — it serves the methodology, plans an install, and verifies it, handing any commands back to the host to run.

Enables conversational analysis of n8n workflows and Make scenarios for silent-failure risks, with tools to explain findings, compare workflow versions, and list rules.

Enables independent, read-only adversarial review of candidate test cases and bug findings, returning a review delta that authoring agents reconcile before writing final artifacts.

Enables AI coding agents to perform real-browser accessibility scanning of localhost pages using Playwright and axe-core, returning WCAG 2.1 violations with structured fix plans.

An MCP server that manages a pool of test accounts, leasing them out one at a time to prevent concurrent session collisions, with automatic reclamation of expired leases.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

Enables verification that a synthesized passage preserves the human-ness of source passages by checking exact copies, logged deletions/reorderings, and flagged unverified transformations.

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

MCP server providing tools to verify task completion (tests pass and changes match claim) and confirm bug reproduction before fixing.

Exposes Semgrep as deterministic, rule-matching analysis tools over MCP so a code-review agent can scan only the lines changed in a diff, scan whole files on demand, and check analyzer availability, version, ruleset, and limits. Results are returned as compact per-finding lines with source snippets suitable as comment anchors, along with counts of suppressed out-of-diff matches.

An MCP server that lets an agent read its own eval results, run suites, explain failures, check drift, and view judge calibration status.

An MCP server that gives AI agents geometric spatial awareness of web page layouts using Playwright, enabling detection of visual occlusion, layout shifts, and spatial relationships.

Translation QA for i18n locale files. Deterministic validators — missing keys, placeholder drift, collapsed plurals, glossary breaches — that need no API key, plus a review tool that hands translation pairs and judging criteria back to the calling agent, so meaning-level review runs on the model your client already has. Translation with your own LLM key is optional. JSON, Flutter .arb, Apple .

Enables AI agents to start, control, and verify local open.mp/SA-MP game servers via MCP stdio, using a headless RakClient to send allowed slash commands and assert round-trip responses.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

Checks a repository's own guardrails and fails any that are present but have stopped refusing anything. Three read-only tools: installation status, per-step verification that issues a receipt, and a tail of the append-only ledger recording every question and answer.

Runs a regular expression on real engines — JavaScript (V8), Python (CPython re), PCRE2 and RE2 — reporting each engine's own compile errors with positions, every match with its groups and named groups, replacement results, and where the engines disagree. It also detects catastrophic backtracking (ReDoS), naming the at-risk part of the pattern, generating an attack string, and timing how long each engine actually takes on it.

Records raw DOM mutations and network events during AI agent browser interactions, enabling detailed debugging and analysis of Playwright automations.

Automates visual inspection of development servers by converting natural language test sheets into Playwright scripts and executing them repeatedly.