"Coolify - An Open-source Self-hosting Platform" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
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.
CareerProof MCP gives AI agents direct access to a professional-grade career and workforce intelligence platform. Two namespaces: atlas_* for HR/TA teams (candidate evaluation, batch shortlisting, competency scoring, interview generation, JD analysis, custom eval frameworks, research reports) and ceevee_* for professionals (CV optimization, career positioning, salary intelligence, market reports). Backed by RAG knowledge from 50+ premium research sources (McKinsey, BCG, HBR, Gartner, WEF)
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.
Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.
SENATRAN: Recall, official-source lookup. Platform-hosted, pay per query with prepaid credit.
Objective-driven deep research: free daily quick search plus MPP-paid cross-source browser reports.
Source-traced evidence research for AI agents. We organise the evidence; you decide.
Know whether an AI agent should REUSE or REFETCH a URL before retrieving it again.
Your private knowledge base: upload documents (.md, .txt, .docx, PDF, images), the platform indexes
Manage your Mistral platform — models, files, batch jobs, agents and RAG document libraries.
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.
Multi-engine search for AI agents. Trust scoring, local corpus, MCP-native. Self-hostable, BYOK.
Self-hostable shared brain for you and your AI agents — docs, flows, meetings, decisions, rationale
Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.
Real-time fact-check, citation verification, and source-freshness for AI agents.
Self-hosted AI-native knowledge workspace with hybrid search, GraphRAG, and MCP.
Explainable graph-retrieval memory engine with an RL-trained management policy.
