"Understanding Structured Thinking" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
What ChatGPT, Gemini and Google answer — structured JSON with cited sources.
Search, browse, and buy AI thinking frameworks from within any MCP client. 597 frameworks drawn from the documented thinking of notable people, plus 24 functional Tools and 7 curated bundles, delivered as .md files and native Claude Skills.
Access Zain Ahmed’s public engineering profile, project case studies, technical articles, and platform engineering resources through MCP tools and structured resources. Hosted Streamable HTTP endpoint at zainahmed.net; public retrieval requires no API key.
mumo is a remote MCP server for multi-model deliberation. Your agent sends a question to models from different labs — Claude, GPT, Gemini, Grok, DeepSeek, Kimi, and more — and gets back their full responses plus typed cross-model reactions. The participating models react to each other directly and explain, in their own words, what they agree with, challenge, or want to explore further. Agents can run a deliberation with `create_deliberation`, wait for results with `wait_for_round`, and steer follow-up rounds with `append_round` using structured signals like KEEP, EXPLORE, CHALLENGE, CORE, and SHIFT. Built for architecture, plan/spec review, strategy, and pre-launch pressure tests. Free tier available. API key required.
HR and recruiting: score a job description, or generate a structured role profile. No API key.
A governed, nonclinical reasoning system that helps people and AI agents make sense of difficult moments and choose a grounded next step. Use Clarity OS for overthinking, emotional activation, uncertainty, decision friction, conflicting priorities, repeating patterns, or difficult conversations. It returns structured, safety-governed clarity while preserving uncertainty, personal agency, and appropriate nonclinical boundaries.
Built for companies. Ready for AI agents. PaperOffice is the headless DMS your agent can actually operate: one MCP endpoint to search, read, upload, extract and sign business documents — no UI, no glue code. What the tools do: full-text and semantic search across workspaces · read existing OCR text without a new job · three-step upload with presigned URLs · AI-OCR (text, line boxes, tables) · structured extraction for invoices and 60+ document types (IDP) · PDF generation from Markdown/HTML · e
Free, no account and no sign-in. Give your AI assistant any website address and it reads the site the way a search engine and an AI crawler would: whether AI crawlers (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and others) may read it, whether its pages can be read without JavaScript, its structured data, titles and meta descriptions, and llms.txt. It answers with what it found, most urgent first, then every check it made. One read-only tool, check_site: it changes nothing, asks no AI engine and stores nothing. Docs: https://therankingfactory.com/developers
Parse unstructured insurance claim text into structured JSON: claim number, type, policy holder, incident, amounts, status, adjuster, next actions, risk flags.
Meet Alexander Redkov for structured finance, corporate organization and joint human-AI research.
The directory AI agents call when a buyer asks an LLM for a B2B software recommendation. Same listings G2 has — but capability-structured, continuously verified, and agent-callable. One listing visible to both audiences.
Shared semantic graph for AI reviews, classification and structured memory across AI assistants.
AI-powered document extraction infrastructure. Convert PDFs, Excel spreadsheets, images, and scanned documents into structured JSON.
Read-only MCP tools for AI agent discovery, structured resources, and NIULAI information.
A high-performance, edge-native Data Refinery Engine built on Cloudflare's serverless AI stack (Workers, Workers AI, D1, KV, Vectorize) designed to continuously ingest unstructured data, refine it into pristine machine-readable structured intelligence, compute semantic diffs, and serve it directly to AI agents via the Model Context Protocol (MCP) and REST APIs.
Background removal, upscaling, face restore, document OCR, table extraction, visual understanding.
Extract structured insights from videos, podcasts, articles, and PDFs with multi-model AI
Return a three-step thinking template. Prompt discarded.
Provides UX capabilities to enhance the design output and understanding of AI systems.
AI takeoff for construction: turn PDF blueprints into structured, traceable quantities.
