"GPT-SoVITS MCP (Model Context Protocol) Integration" 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.
Machine-exclusive web distillation MCP server for AI agents. Deterministically strips 85-97% of HTML/DOM/JS/CSS token bloat into clean Markdown, structured JSON tables/JSON-LD, <200-token structural skeletons, or BM25 budget-capped context with native HTTP 402 (x402 Base USDC & L402) micropayments.
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Verified Texas business context for AI agents: legal entities, affiliates, licenses, new openings.
Bring your saved preferences, project decisions, and useful context into your next AI conversation.
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.
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
The right context at the right time, from the world's leading data providers. One API. 800+ tools.
The context marketplace: expert guided journeys your assistant runs step by step.
Fresh context for agents. Ask, search or follow stories. Each fact cites a Synorb Manifest.
Persistent project context for xAI Grok. IANA-registered .faf format.
The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.
Reduce supplied context and check caller-declared, source-specific exact evidence retention.
Search hub knowledge and memories, read saved context, and create or update hub content.
Tenant-scoped evidence intake and controlled AI context over MCP.
Turn a GitHub repo or docs site into agent-ready context: pack it or search it, over MCP.
One semantic search across your sites, Drive, Notion, email, files and Basecamp.
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.
Human-authored personal context before AI guidance, built through private structured reflection.
Compact, citation-verifiable public web context for AI agents, paid per use with x402.
