"Automated cleanup tools" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Cloud or self-hosted knowledge for AI agents: hybrid search, reranking, GraphRAG, scoped MCP tools.
Deterministic AI agent microtools, no accounts/API keys. fetch_extract: 98% token cut. 38 tools.
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).
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 first low-latency wire service purpose-built for AI agents. Ingests 54+ public APIs and 71k RSS feeds across 232 countries, outputs CWF (Cognitive Wire Format) – 80% shorter than JSON, sub-second WebSocket delivery. 9 MCP tools: get_latest_signals, search_signals, get_fused_signal, scope_signals, get_facet_manifest, list_facets, get_related_signals, list_data_sources, get_billing_profile. 26 citable fusion products with verifiable formulas – no black-box scores.
AI-first file sharing and collaboration. 251 tools give agents a full workspace: file storage, branded shares, comments, workflows, and built-in RAG. 50GB free, no credit card.
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.
PDF/Word/Excel/HTML to clean Markdown for LLMs and RAG. Keys $19/mo; 50 free calls a day.
x402 clean article text and metadata for AI/RAG. $0.002 per successful article.
x402 PDF text, pages, and metadata for AI/RAG. $0.0015 per successful PDF.
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.
Observe MCP tools, verify repeated reads, then try bounded exact reuse for free.
Free OpenAI-compatible inference with signed provenance receipts and 3 focused MCP tools.
Shared knowledge base for AI agents. Semantic search across agents, no setup required — just a URL.
100+ MCP tools for AI agents: content metadata, trade intelligence, business-expertise analysis.
At BittleBits, we build AI visibility and Generative Engine Optimization (GEO) tools that help companies optimize their content for AI systems like ChatGPT, Claude, Gemini etc. We’ve developed a proprietary AI model that analyzes how AI systems evaluate, trust, and cite content in conversational responses, helping brands improve discoverability across AI-powered search.
Persistent cloud memory for Ai coding assistants. 33 MCP tools, 85% accuracy on LoCoMo benchmark. Semantic search, auto-skills, knowledge graph, quantum-safe encryption. Works with Claude Code, Cursor, Windsurf, and any MCP client.
MCP server providing AI security tools: prompt injection detection, PII scanning, and RAG input validation. Works with Claude, Cursor, and any MCP-compatible client.
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.
