"Information or resources about data" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Unstructured document processing for LLM pipelines. Upload as PDF/DOCX/TXT any supported files, extract structured data (PII-redacted), build LLM-ready datasets, and search/export results — all via MCP tools (document.process, job.status, job.result, dataset.build, dataset.search, dataset.export).
Search agent-ready sites or fetch one site's report; every capability probe-verified, dated.
Cloud or self-hosted knowledge for AI agents: hybrid search, reranking, GraphRAG, scoped MCP tools.
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
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.
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.
Direct access to 60+ scraping and search tools. Extract structured data from Google (Search, Maps, Trends), Amazon, Airbnb, Social Media, and any web page directly into your AI agent.
Give your agents your team's real data — read the shared graph, propose actions your team approves.
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.
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.
Governed data discovery, exact queries, decisions, simulations, and runtime utilities over MCP.
Any URL to clean text, markdown, or JSON for LLM/RAG pipelines.
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.
Historical market memory for AI agents using semantic vector search across years of financial market data. Discover similar market regimes, price patterns, and market context for quantitative research and algorithmic trading.
Decide whether an agent should reuse cached URL knowledge or fetch the resource again.
Turn a GitHub repo or docs site into agent-ready context: pack it or search it, over MCP.
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.
A high-performance, edge-native Data Refinery Engine built on Cloudflare's serverless AI stack (Workers, Workers AI, D1, KV, Vectorize) designed to continuously ingest unstructured data, refine it into pristine machine-readable structured intelligence, compute semantic diffs, and serve it directly to AI agents via the Model Context Protocol (MCP) and REST APIs.
Check claims against a fact-store: consistent, contradicts, or unverifiable — with a receipt.
