"Files" matching MCP servers:

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

Read-only MCP view of a repository's CRAP scores: cyclomatic complexity joined to the branch coverage the repo's own test command writes. Nine tools hand an agent the worst function to fix next with its source, uncovered lines, change-coupled files and near-duplicates.

Enables read-only analysis of FST waveform files, including signal value queries, timing measurements, event search, latency analysis, and PNG plot generation using human-readable time addressing.

Enables AI assistants to inspect generated .docx and .pdf files before delivery, extracting structural, typographic, spacing, and language facts so formatting errors can be caught automatically.

Feedback ingestion for AI agents. Record your screen and talk; your agent does the rest — files the bugs, writes the spec, builds the backlog.

Creates, validates, audits, and repairs PowerPoint .pptx files against the OOXML spec, allowing users to generate spec-compliant slides from templates.

Enables passive security scanning of HAR files from QA test automation to detect missing security headers, insecure cookies, CORS misconfigurations, and leaked secrets, without making any live requests.

MCP server that validates dashboardbase setup files and widget endpoint responses against the dashboardbase JSON contract, reporting errors and warnings before deployment.

Audits Excel workbooks by tracing cell dependencies and detecting circular references, volatile functions, and other formula risks, enabling natural-language audit queries on local files.

A ruthless, read-only code review MCP server that analyzes code produced by AI coding assistants, catching missing requirements, security vulnerabilities, edge cases, and performance issues without ever modifying files.

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

Enables AI agents to inspect Shadow Monitor capture files locally, with tools to load bundles, find errors, search network requests, and replay user actions.

Enables Claude to perform thorough code reviews by integrating with Codex and Gemini CLIs to provide senior-level feedback on code quality, security, performance, and best practices. Supports reviewing code snippets, individual files, or entire directories with automatic detection of available review tools.

An MCP server for WCAG accessibility auditing in AI coding agents, providing tools to audit HTML, files, URLs, and diffs, plus a prompt for React component auditing.

ocal-first, read-only MCP server that audits repository test architecture across ten language ecosystems. It returns deterministic evidence-backed findings, blockers, rankings, and repository-native test plans without modifying source files.

AI-powered characterization test generator that reads Python functions or class methods, synthesizes inputs, captures behavior in a sandbox, and emits pytest files to lock legacy code behavior for safe refactoring.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.

MCP server for API test case generation from Swagger/OpenAPI specs. Parses Swagger 2.0 and OpenAPI 3.x, generates test cases across 8 categories (positive, negative, boundary, auth, security, idempotency, pagination, business logic), and exports to Postman, TestRail, Allure, k6, pytest, Gherkin, and CSV. Supports internal corporate APIs with auth headers. Auto-saves export files to your working di

Enables AI agents to run CP/M, MP/M, and DOS packages on Z80/x86 emulators, inspect byte-exact results and files, and debug the emulators themselves over the Model Context Protocol.

Enables AI assistants to analyze and inspect RenderDoc capture files, providing tools to examine draw calls, textures, buffers, and shader information. It allows developers to perform graphics debugging and resource analysis through natural language interactions.