"A tool for critical thinking and devil's advocate analysis of AI model plans" matching MCP servers:

Enforces 21 critical rules derived from 96+ documented failure patterns to prevent common AI assistant mistakes. Provides automatic compliance checklists, rule summaries, and auto-updates.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Provides search and retrieval over a local database of Pathfinder 2e rules. Enables Claude Code to answer rules questions with cited, accurate answers from fetched entries.

Provides verified, up-to-date model IDs, pricing, and specs for over 100 models across 19 providers, preventing AI agents from using outdated or hallucinated model names.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

A Bun-based MCP server that allows AI models to query Swagger/OpenAPI documentation from local files or remote URLs. It enables users to search for APIs, retrieve detailed endpoint definitions, and fetch schemas to facilitate code generation and API integration.

An MCP server that helps transfer C4 diagrams from DrawIO and PlantUML into a DocHub architecture repository.

Provides a live, audited catalog of AI models from NVIDIA NIM, OpenRouter, Nous Portal, and other providers, enabling search, retrieval, and usage examples via MCP tools and resources.

Optimizes EDT MCP tool descriptions by replacing verbose documentation with concise summaries stored in SQLite, reducing context usage while allowing on-demand retrieval of full tool guides.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

A smart documentation system that helps AI assistants understand and follow your project's conventions by automatically discovering, routing, and managing AI_README.md guide files.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Enables querying a compressed knowledge graph of the NVIDIA AI developer stack, allowing users to traverse declared dependencies, prerequisites, and relationships across 20 domains via read-only MCP tools like query_ckg, get_prerequisites, and search_concepts.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

MCP server for EU AI Act compliance analysis — classify any AI system or workflow against Regulation (EU) 2024/1689, updated with AI Omnibus 2026.

Integrates IDEs with the 1C:Напарник API, providing code analysis tools and documentation search for 1C.

A self-synthesizing AI knowledge wiki that provides a read-only MCP surface for external agents to trace the wiki content and graph.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.