"Information about MariaDB, an open-source relational database" matching MCP connectors:
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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.
Query your Postgres from ChatGPT or Claude without exposing the database or handing over credentials. Run npx boltschema connect next to your database and it dials out over HTTPS — no inbound firewall rule, no open port, works with localhost and VPC-private databases. Read-only is enforced by a SQL guard, a Postgres READ ONLY transaction, and a scoped role generated for you.
Primary-source SEC filing intelligence for AI agents, with exact evidence and provenance.
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 Fragments — two tools for the queries an agent can't place, both built to decline rather than guess. resolve_fragment takes a half-remembered, cross-source query ("a musician who became famous for stopping performing") and returns a grounded answer, ranked web sources to confirm by eye, or an explicit no-resolution. verify_claim takes a specific factual assertion and returns supported, partially_supported, insufficient_evidence, or unsupported, with cited evidence and a stated_limits field that is always present. There is no confidence score — insufficient_evidence fires freely, and unsupported requires a source that explicitly contradicts, never mere absence of confirmation. Every verdict is decide-by-eye: "supported" means current web sources confirm it, not that the claim is true. Calibrated against 18 known claims before release. Free, no signup. Streamable HTTP (MCP 2025-11-25). Read-only.
A personal RAG database you build from chat, so AI creates work that sounds like you.
Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.
Decide whether an agent should reuse cached URL knowledge or fetch the resource again.
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.
AI product expert answering from live source code, with sources and a verification status.
Read and search exact public source URLs with stable paragraph citations.
SENATRAN: Recall, official-source lookup. Platform-hosted, pay per query with prepaid credit.
Source-traced evidence research for AI agents. We organise the evidence; you decide.
Objective-driven deep research: free daily quick search plus MPP-paid cross-source browser reports.
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.
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.
Explainable graph-retrieval memory engine with an RL-trained management policy.
Remote ChromaDB vector database MCP server with streamable HTTP transport
Real-time fact-check, citation verification, and source-freshness for AI agents.