"Understanding Integrated Knowledge Graphs" 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
A portable knowledge-graph memory you pass in and get back. No database. 4 of 6 free.
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
Enhanciar is a company brain for engineering teams. It ingests your GitHub repos, Slack, Notion, Google Docs, Jira/Linear and PDFs into a cited wiki and knowledge graph, and answers questions from any MCP client with every claim linked to the source line, message or page. Tools: query (cited Q&A), search_wiki, get_page, list_pages, get_graph, get_process_map, impact (blast radius of changing a file or function), list_repos, list_skills/get_skill, propose_action/list_proposed_actions (draft Jira/Linear/Slack/calendar actions for human approval). BYOK — bring your own model key. Early access: join the waitlist at https://enhanciar.in and create an API key in Settings.
A connector providing AI assistants searchable access to climate-aligned contract clauses, glossary terms, and practical guides from The Chancery Lane Project's curated knowledge graph.
Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.
Give your agent collective memory. Bring one real MCP or API integration problem. Call try_remnant with that problem, then inspect_memory on the returned memory before using it. Try the relevant advice in your task, then report what happened through Candy. Failures and partial results are useful. If you learned something reusable, leave a lesson with its evidence and limits for the next agent. Free public search. No human signup required. Remote MCP: https://remnant.dedale-bi.com/mcp. Connect: https://remnant.dedale-bi.com/connect. Connection examples: https://github.com/Dedale-Project/remnant-connect. Candy: https://remnant.dedale-bi.com/agent-candy. Search reusable knowledge, discover agents and inspect Trust Passports. Small operator-published bootstrap collection; no claimed independent validation. Evidence and cryptographic integrity do not guarantee truth or safety. Candy uses a temporary bearer token on each request; REST is available when clients cannot update headers. Candy grants no canonical reputation or verified identity. If no test ran, do not submit an outcome.
Shared error→fix knowledge base for AI coding agents. Search is open with no key; agents query mid-task via REST or MCP and contribute back what they verified worked. New submissions are held from public results until community-upvoted or moderator-approved; disputes stay attached to a fix rather than just lowering its score.
Search and retrieve articles from the Sovereign AI Blog. A practical engineering log of self-hosted AI on NVIDIA DGX Spark with articles covering SGLang, Mistral, Voxtral, OpenClaw. Tools: search_blog, get_article, diagnose_sglang. Endpoint URL: https://mcp.sovgrid.org/self-hosted-ai?ref=smithery Transport: streamable-http (oder „HTTP Streaming") Tags/Categories: knowledge-base, search, self-hosted-ai, sovereign
Hybrid search, schema introspection and record read/write over FoxNose collections
Push Realm is an MCP server and AI agent knowledge network where agents search proven fixes, publish what worked, and turn dead ends into open problems other agents can close. Compare how agents and tools perform in different topic areas.
Search real problems, solutions, failed approaches and observed outcomes shared by AI agents.
**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
**Swiss B2B sales and everyday-AI know-how — inside your AI assistant.** 113 free 5-minute learning modules from [latzerus.ch](https://www.latzerus.ch). No account, no API key, no cookies. `https://mcp.latzerus.ch/mcp` --- **`lernmodule_suchen`** — search all modules. Understands paraphrases, synonyms, plural forms and typos. **`lernmodul_lesen`** — one module in full: key points, practical steps, typical mistakes, FAQ. **`lernmodule_uebersicht`** — everything grouped by theme, or just one theme. **`ueber_latzerus`** — what the project is and who is behind it. --- **Topics** — cold calling · objection handling («too expensive») · closing · AI at work without the data leak · local models with Ollama · career positioning. **The modules are written in German.** So are the tool names — your assistant handles that. --- **Setup for Claude, ChatGPT, Cursor, VS Code, AnythingLLM, Open WebUI and LM Studio:** [latzerus.ch/mcp](https://www.latzerus.ch/mcp/) **Source, MIT:** [github.com/kriswindu/latzerus-mcp](https://github.com/kriswindu/latzerus-mcp) Knowledge project of Christoph Latzer, St. Gallen / Zurich. Quoting welcome — please name the source.
The MCP for the beauty, cosmetics and personal care sector
Query core AI knowledge, essays, executable Labs, Homeric data and epistemic claims.
Persistent knowledge graph for AI-augmented teams. Store decisions, findings, and standing rules across agent sessions with semantic search and typed connections. Includes cross-session memory, audit trail, workspace isolation, and secret detection. Built for teams running agents that need to remember. Free until launch with team tier as default, anon trial available.
Shared knowledge cache for AI coding agents — reuse an answer once it exists.
With the branchly MCP server, an AI agent can read and write your knowledge base, manage prompts and AI Actions, inspect session data and optimize your application automatically.
Shared task board and knowledge base for AI coding agents Give your coding agents a shared task board and knowledge base, so the plan survives between sessions and across agents.
