"OpenAI's Web Retrieval Infrastructure" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Your Recipes, Beautifully Kept. weReci MCP server lets Claude and other MCP clients work with your personal weReci cookbook, the recipes you've imported from the web, social video and scanned family books. Interactive UI in the chat. weReci supports MCP Apps, so in clients that support it, tools return live views instead of plain text: recipe cards, shopping lists and your recipe graph. Clients without MCP Apps support get the same results as text. Find and read recipes: search your collection in plain language, open any recipe in full, or get an overview of what's in your cookbook. Cook with them: scale a recipe to any serving count, with cooking adjustments as well as amounts. Get substitution suggestions with ratios and caveats. Explore connections: browse your recipe graph (shared ingredients, techniques and cuisines), trace the connection between two recipes, and look up where a dish sits on the cuisine map. Themed collections: list the themed groups weReci curates from your cookbook, or ask it to reshuffle them. Shop: build a shopping list from one or more recipes, add or update items, and read the list back. Share: email a recipe to someone. Longer jobs like conceit reshuffles run in the background, with tools to check their progress. Everything is scoped to your own cookbook, or to a shared one you've joined.
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
Canonical vocabulary server for autonomous business design. Exposes the Arco Lexicon as seven MCP tools: term lookup, related terms, alignment verification, citation formatting, source retrieval, term listing, and term suggestion. No authentication required. Streamable HTTP transport.
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
Deterministic contextual decision arbitration and action routing for autonomous software. Takes current state, context, or intent plus caller-supplied candidate actions, state transitions, routes, refusals, escalations, tools, or models and returns a deterministic ordered candidate field. Also provides persistent machine representations for memory, retrieval, indexing, and downstream coherence measurement.
**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
MCP-native Trust Infrastructure for AI Agents. Persistent encrypted memory with Trust Quotient.
Give your agent web search and authoritative datasets: S&P Global, FRED, OECD, SimilarWeb & more.
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.
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.
Save and organize web finds in persistent, user-controlled collections for AI assistants.
Norwegian open-source community wiki (2,290 articles, 2008-2022) as a signed KCP knowledge web.
Forensic archive of javaBin & JavaZone origins (1998-2007) as a signed KCP knowledge web.
Thor Henning Hetland's signed knowledge web: plan, load and verify ed25519-signed KCP units.
Knowledge Base von designare.at – Michael Kanda, Web & KI aus Wien. Semantische Suche über RAG.
Append-only decisions with provenance, supersession, retrieval, and audited MCP actions.
Intelligent context infrastructure for AI teams: knowledge graph, sessions, tasks, documents.
Brand health & trend footprint across PSFK expert graphs with citable sources, not web summaries.
Diffbot MCP — Knowledge Graph company enrichment + web content extraction (diffbot.com)
