"Understanding Prompts or Prompt Engineering" matching MCP connectors:

For queries a model can't confidently place: resolves or declines. Built to decline, not guess.

Turn a GitHub repo or docs site into agent-ready context: pack it or search it, over MCP.

Semantic search over the Stoic corpus — Marcus Aurelius' Meditations, Seneca's essays, and Epictetus' Discourses, Enchiridion and Fragments. Search by theme or citation, fetch any passage, or get the daily reflection. Public domain translations, no auth.

Know whether an AI agent should REUSE or REFETCH a URL before retrieving it again.

Check claims against a fact-store: consistent, contradicts, or unverifiable — with a receipt.

Multilingual YouTube → Knowledge Pack engine. Paste a video URL and get a structured pack — summary, key ideas, glossary, quiz, transcript with timestamps — in Spanish, Portuguese, German, or English. Anonymous endpoint plus OAuth-gated tools for library search, RAG Q&A on a single pack, and Anki export.

The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.

Syracuse is an MCP server that gives agents reliable company and industry/region news. Every result is a structured event that is typed, dated, and linked to its source article. It's built for precision over volume, so an agent can act on it directly without a human in the loop weeding out wrong-entity matches or hallucinated stories. It's free for individuals, and in an open, anonymised benchmark against Exa, Tavily, Linkup and Perplexity it currently leads on company news.

Real-time web search with answer-ready results for Claude, Cursor and any MCP client. A Tavily alternative: same speed, 20.2% fewer tokens, higher answer quality (60.7% of decided duels won) on a public benchmark. Hosted on mcp.serpdive.com or npx serpdive-mcp.

Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.

Persistent memory for AI assistants. Save once; recall from Claude, ChatGPT, or any MCP client.

Illumora Craft — evidence-augmented prompt compile for agents via remote MCP (OAuth) or local stdio.

MCP server providing AI security tools: prompt injection detection, PII scanning, and RAG input validation. Works with Claude, Cursor, and any MCP-compatible client.

LLMtoMD is the memory layer for AI coding agents. It converts any document — PDF, DOCX, slides, spreadsheets, images, audio, even whole websites — into clean, structured Markdown, then exposes it over MCP so your agent can search your FRDs, specs, and API docs on demand instead of re-reading (or forgetting) them.

Agent search: query-tailored web/news/paper/podcast segments, not full pages or links.

Connect Claude, Cursor, or ChatGPT to your business data. Ask questions, get answers.

Connecting LLMs and AI agents to real-time production data shouldn't mean writing endless boilerplate middleware. BoltSchema automatically converts your PostgreSQL into secure, production-ready, and hosted Model Context Protocol (MCP) servers. Save days of engineering time, handle JSON-RPC schemas automatically, and let your AI securely query the exact data context it needs in under 60 seconds.

MCP memory server with shared team workspaces, typed knowledge chunks (decision, finding, convention, state, question, reference), role-based access, and cross-tool support for Claude, Cursor, and Codex. The only MCP memory server built for engineering teams. Features automatic deduplication, two-layer retrieval (LLM KB selection + hybrid vector/BM25/RRF fusion), a web dashboard with knowledge graph visualization, and attribution tracking. Zero server-side LLM costs.

Manage, version, and publish LLM prompts with blocks, variables, and evaluations.

Make your knowledge agent-ready. Connect docs from Confluence, Notion, GitHub, Dropbox, or Google Drive — any AI agent searches them via one MCP endpoint. 3 retrieval modes: vector search, broad search, and full document access. The agent decides how deep to dig.