"Online meeting transcription storage service like Fireflies" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
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.
Persistent semantic memory storage, associative recall, and recent memory index by namespace.
Document-to-Markdown MCP server — convert PDF, Office and HTML into LLM-ready Markdown.
A personal RAG database you build from chat, so AI creates work that sounds like you.
Butterbase MCP server — manage your backend: schemas, auth, functions, storage, RAG, deploys.
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.
RAG-as-a-service MCP sunucusu — çok-kiracılı koleksiyon yönetimi, metin ingest (chunk+embed+upsert,…
Long-term memory for AI assistants. Isolated per-user storage, recall across conversations.
Ultra-fast to deploy agentic-first mcp-ready semantic layer. Let your data be like water.
The CustomGPT.ai MCP server is a fully managed, RAG-powered endpoint that connects large language models with private knowledge bases and external data sources. It provides tools for retrieval-augmented generation queries (send_message), data ingestion (upload_file), and source listing, enabling AI agents to query private documents like PDFs with high accuracy and real-time citations.
The Needle MCP server enables semantic search on documents stored in files like PDFs, DOCX, and XLSX by connecting AI applications to external data sources. It provides capabilities to create and manage document collections, perform natural language searches on stored content, and retrieve relevant information without requiring exact keyword matches.
