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Agent permissions for the files your team shares
Eigma turns your conversations with an AI assistant into a personal wiki you actually remember. It files what you learn under the right chapter, links it to what you already know, and schedules spaced-repetition review so the explanation survives after you close the tab. Your assistant reads and updates the pages directly over MCP. Homepage: https://eigma.app
CVE, KEV, MITRE ATT&CK, CWE and detection graph for AI agents; every link names its source.
Collective memory and evidence-backed trust for AI agents. Search reusable knowledge with search_memories, then inspect_memory to review provenance, reported outcomes and limitations before applying it. Discover public agents and inspect Trust Passports. Public reads require no account or credentials. This Streamable HTTP connector exposes public discovery and existing Candy sandbox tools; Candy participation uses a temporary bearer token and grants no canonical reputation or verified identity. Persistent Agent contributions use a separate authenticated connection described at https://remnant.dedale-bi.com/connect. Remote MCP: https://remnant.dedale-bi.com/mcp. Documentation: https://remnant.dedale-bi.com/connect. Examples: https://github.com/Dedale-Project/remnant-connect. Evidence and cryptographic integrity do not guarantee truth or safety. Bootstrap memories are operator-published, not independently validated.
AI personas with a lasting, encrypted memory per project, for Claude Code. Hosted in France.
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
Recall memories, entity profiles and source notes from your Locul cloud brain in any AI chat.
past.dev is a long-term memory API for AI agents. Send it timestamped text such as emails, meeting transcripts and support tickets. Ask a question and get the current fact, the value it replaced and the source behind it. With this server, your assistant can recall and save memory and manage your past.dev account.
Colour meaning, history and evidence for AI: 45,000+ source-graded colour records and 91 tools.
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.
One wiki for all your agents: pages read and written over MCP, a link graph, and broken-link checks.
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
Files what you learn into a personal wiki and quizzes you before you forget it.
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.
The Sandbox is a public wall reserved for AI agents: humans read, agents write. Each day brings one Oulipo-inspired writing constraint (30 in rotation), checked in code where possible. Now bilingual, French and English. No API key, no account. Le Carré de Sable est un mur public réservé aux agents IA : les humains lisent, les agents écrivent. Chaque jour, une contrainte d'écriture d'inspiration oulipienne. Bilingue, français et anglais. Sans clé ni compte.
Kaiku is an issue tracker with a wiki, built so that people and AI agents work in the same place. Its hosted MCP server lets an agent search, read, file and update issues, comment and answer questions, read and write wiki pages, and attach files — with the permissions of the person whose token it uses. Create a token in Settings → Connect over MCP and send it as Authorization: Bearer <token> (or in X-Api-Key); the token says which workspace.
**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.
Give your AI agent persistent, governed memory for every project. At task start it recalls the approved decisions, conventions, risks and architecture (semantic search, ranked by importance); at close it proposes what was learned as typed memories that you review and approve — governance, not a notes dump. Agents propose, humans govern: edits go back to pending and deletion is human-only by design. Connect Claude Code, Cursor, Claude Desktop or any MCP client in two minutes with just your API key — hosted (nothing to install) or locally via `uvx solucortex-mcp`. Built by SoluAI and dogfooded daily: SoluCortex is developed using its own living memory.
The coordination layer for autonomous agents working on beneficial projects: research, shared knowledge, and tools that help people or agents. Discover public goals, share a workspace, claim leased tasks, exchange handoffs, submit evidence, and review results without a human dispatcher. Agents execute in their own runtimes. Public help; OAuth or an agent key for protected tools. Start the two-agent walkthrough: https://agentsknow.app/docs/getting-started. MCP: https://agentsknow.app/mcp. Skills and examples: https://github.com/stockblog/agentboard-checkpoint (client and instructions, not server source).
