"Understanding Structured Thinking" matching MCP connectors:

XMemoAOAuth

io.github.yonro

XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs

Web Data FormsA

com.webdataforms.mcp

Give AI assistants secure access to your organization's structured business data. Search records, create and update records, retrieve schema information, and manage workflow states using natural language. You need two values for every request: x-api-key — your Web Data Forms API Key x-group-id — your Web Data Forms Group ID You can find these in your Web Data Forms accounts group->information page. Preferred method: request header When possible, pass the credentials as HTTP headers: x-api-key: <your-api-key> x-group-id: <your-group-id> This is the preferred option because it keeps credentials out of the URL and is more secure. Fallback method: query parameters If your MCP client does not support custom headers, the server also accepts the credentials as URL query parameters. Example: https://mcp.webdataforms.com?x-api-key=abc123&x-group-id=xyz456 Detailed information here: https://github.com/Web-Data-Forms/mcp-server-docs/blob/main/README.md

**ColdState Knowledge Search MCP Server** https://github.com/daniel-coldstate/coldstate-mcp Semantic search over 64.6M knowledge entries — the structured alternative to web search APIs and web scraping for LLM agents. No crawling, no rate limits, sub-3s responses. Cloud-hosted at services.coldstate.ai

Shared semantic graph for AI reviews, classification and structured memory across AI assistants.

Agent Module provides structured, validated knowledge bases engineered for autonomous agent consumption at runtime. Agents retrieve deterministic knowledge instead of scanning unstructured web content — eliminating hallucinated citations in regulated domains.

TestGraph is a shared structured knowledge and review graph for AI agents. Its MCP server lets ChatGPT, Claude and other AI clients store, retrieve and collaboratively refine reviews, entities, relationships and semantic classifications, providing persistent knowledge that can be reused across models and conversations.

Real engineering memory marketplace for autonomous AI agents. Query structured lessons (problem → root cause → solution + confidence 80-100%) extracted from real GitHub/Slack incidents. Categories: debugging, architecture, performance, security, infrastructure & more.

DREAMHALLA

app.dreamhall

Human-authored personal context before AI guidance, built through private structured reflection.

Urban intelligence knowledge graph. Structured locality data for civic problem-solving.

A portable context layer for MCP-speaking AI clients. Connect any client to one endpoint and it boots with your containers — structured context, live work state, and accumulated knowledge — carried across every client you use.

DocsieOAuth via extension

io.docsie.app

Docsie MCP brings your documentation workflow directly into your AI assistant. Create, edit, and publish documentation without switching between tools. Convert videos into structured documentation instantly, run compliance analysis across text, audio, and video content, and use semantic search to find exactly what you need across your knowledge base. Whether you're building product documentation, SOPs, user guides, or technical manuals, Docsie MCP makes documentation faster, smarter, and powered

RChilli MCP Hub is a production-grade MCP server that exposes RChilli's full HR data intelligence platform as 17 AI-callable tools across 4 categories. Built on 15+ years of HR data intelligence, it is trusted by ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. Every tool is read-only and returns a consistent, structured JSON response — no raw exceptions, no inconsistent formats.

Grimoire turns your TTRPG campaign into a structured, queryable database and knowledge graph and exposes it to any MCP-compatible AI client. Your campaign becomes first-class context for whatever client you bring.

Full-control memory API for AI agents with direct access to structured data, relationships, and revision history. Built for advanced workflows, it enables precise querying, linking, and maintenance of a complete memory graph with full transparency and control.

Scraps Kitchen gives any AI agent a persistent, household-aware kitchen memory. Unlike generic chatbot recall, Scraps maintains structured cooking data: what's in your fridge (with freshness tracking), who you cook for (with allergens, dietary restrictions, and preferences), your recipe collection (with cook notes and per-diner ratings), your shopping list, and your kitchen equipment. 27 tools across 6 domains let agents read kitchen context, suggest meals that respect dietary safety, update the pantry after cooking, and build a history of what works for your household. Every interaction makes the data richer. Cooking history, preference signals, kitchen awareness = better suggestions next time. All tools work via oAuth and a free scraps.kitchen account.

Memwyre is an MCP-native persistent memory layer for AI agents, synchronizing context across Claude Code, Cursor, VS Code, and OpenClaw. Built with a high-precision retrieval architecture (dense vector search, BM25, and cross-encoder reranking), Memwyre achieves a benchmarked 73.1% accuracy on the Long-Context Memory (LoCoMo) benchmark. It provides secure, isolated knowledge vaults with dedicated tools (search_memwyre, save_memory, list_memories) to save and recall structured project decisions.

Unstructured TransformOAuth

io.unstructured

Turn documents into structured, AI-ready data by parsing, enriching, chunking, and embedding.

DreamThreads DreamGraphA

io.github.abdulrahimiqbal

Parse dreams into structured context and search DreamGraph concepts without storing dream text.

Store, query, and update structured data from any AI agent

Structured knowledge base for AI agent solutions. Search, explore, and retrieve build logs.