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"Git MCP (Model Context Protocol) Server" matching MCP connectors:

GET /v1/connectors – MCP directory API reference

Matching Connector Tools:

  • 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

  • Vigilia watches your live app, explains every problem in plain language and writes the fix prompt. Your AI fixes it; Vigilia confirms with real traffic. Vigilia watches web apps that are live with real users, including apps built with Lovable, Bolt, v0, Cursor and Claude Code. It catches errors, failed requests and downtime, explains each problem in plain language, and writes a fix prompt for it. Connect Vigilia to Claude and ask what's broken. Claude lists your open incidents worst first. For each one it reads the plain-language diagnosis, who it affects, the technical evidence (error, page, failing request, stack frames and what the visitor did right before) and Vigilia's fix prompt. In Claude Code or another coding agent, Claude can then fix the cause in your own codebase. Once you've deployed, it marks the incident fixed, and Vigilia watches real traffic to confirm the error stayed away. If it comes back, the incident reopens as a regression. You can also ask how an app is doing (uptime, open incidents, today's traffic), get the exact install snippet for a new project, and check that a live site is running Vigilia. Vigilia never reads or changes your code: the fixing happens in your session, by your AI, in front of you. The only tool that changes anything is marking an incident fixed (the install check just records its result on the app), and you can connect with read-only access. Your data is stored in the EU. Emails, tokens and card numbers are stripped from what visitors' browsers send, and only that scrubbed error context is sent to Anthropic to write the diagnosis. Requires a Vigilia account. The free plan covers one app; reporting backend errors (Supabase, Next.js routes, Workers) is part of Pro.

  • Real-time Israeli rental listings, pricing estimates, and neighborhood intelligence across Tel Aviv and central Israel. Search 5+ deduped sources with hourly liveness, view specs, estimate fair-market rent, and explore local transit and area context directly inside your agent.

  • Every AI. One room. The open hub where the world's AI agents meet, work together and exchange.

  • Edit and publish your FramerToNextJS sites (converted Framer or AI-built) from Claude, Cursor or Codex. 19 tools: read pages, rewrite copy, restyle elements, add sections and pages, design Studio sites, manage CMS collections and items, then publish to your own host. OAuth with a read-only option, and MCP runs no model on FNJ's side. Requires an FNJ plan (Lifetime or any AI builder plan).

  • Fuzzbucket is an AI-native creative workspace that enables AI agents to generate on-brand images, videos, audio, and marketing copy. Connect your brands, access persistent brand context, manage creative assets, and execute marketing workflows directly from AI assistants through MCP. Fuzzbucket helps agents turn ideas into consistent, production-ready marketing content without starting from scratch.

  • The CNAPS.ai MCP Server lets Claude build and run AI image, video, and text pipelines mid-conversation — no dashboard, no manual node-wiring. Describe a task in plain language (e.g. "upscale this photo 4x") and Claude selects the right model(s), wires a pipeline, and runs it.

  • XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs

  • # Supadata **Supadata ([supadata.ai](https://supadata.ai)): video transcripts, social media metadata, AI video analysis, and web scraping for AI agents, behind one MCP server.** [Supadata](https://supadata.ai) turns YouTube, TikTok, Instagram, X (Twitter), and Facebook videos, plus any web page, into clean text and structured JSON that an LLM can use. Your agent passes a URL and gets back a transcript, metadata, extracted data, or Markdown. One account, one response format across every platform. This repository is the integration front door. The product itself lives at [supadata.ai](https://supadata.ai); the remote MCP server lives at `https://api.supadata.ai/mcp`. ## What you can build with it - **Video to text**: fetch transcripts through the [YouTube Transcript API](https://supadata.ai/youtube-transcript-api), [TikTok Transcript API](https://supadata.ai/tiktok-transcript-api), [Instagram Transcript API](https://supadata.ai/instagram-transcript-api), and [X (Twitter) Transcript API](https://supadata.ai/twitter-transcript-api). When a video has no captions, the [AI Transcription API](https://supadata.ai/video-transcript-api) generates one, and it works on direct video file URLs too. - **Video and channel metadata**: titles, descriptions, authors, views, likes, and comments as clean JSON, a simpler [YouTube Data API alternative](https://supadata.ai/youtube-api) that also covers TikTok, Instagram, X, and Facebook. - **Structured data from video**: give a prompt or a JSON schema and the [Video Analysis API](https://supadata.ai/video-analysis-api) returns structured output that accounts for visuals, audio, and context. - **Web context**: scrape any page to Markdown, map a site's URLs, or crawl a whole site for RAG and research. See the [web scraping docs](https://docs.supadata.ai). ## Verify the connection Ask your client: > Get the transcript of https://www.youtube.com/watch?v=dQw4w9WgXcQ and summarize it in three bullet points. You should see a `supadata_transcript` tool call and a real summary. ## What the tools do The server exposes 9 tools in four groups. - **Transcripts**: `supadata_transcript` (get a transcript from a YouTube, TikTok, Instagram, X, or Facebook video URL, or from a direct file URL; uses existing captions when available and falls back to AI transcription when there are none), `supadata_check_transcript_status` (poll an asynchronous transcript job by its job ID; long videos return a job instead of an immediate result). - **Metadata**: `supadata_metadata` (title, author, and engagement stats for a social media post or video). - **Video analysis**: `supadata_extract` (start an AI structured-data extraction job for a video, driven by your prompt or schema), `supadata_check_extract_status` (poll an extraction job by its job ID and read the extracted data). - **Web**: `supadata_scrape` (scrape a web page and return its content as Markdown), `supadata_map` (map a website and return the list of URLs found), `supadata_crawl` (start a crawl job for a whole site), `supadata_check_crawl_status` (poll a crawl job by its job ID and read the crawled pages). Transcripts of long videos, extractions, and crawls are asynchronous: the first call returns a job ID, and you read the result with the matching `check_*_status` tool. Costs: tools spend your regular Supadata credits at the same prices as the API. A native transcript costs 1 credit, an AI-generated transcript costs 2 credits per minute of video, and checking job status is free. The free plan includes 100 credits a month with no credit card required. The [pricing page](https://supadata.ai/pricing) has the details. ## Or skip MCP The same capabilities are available as a plain REST API with [TypeScript and Python SDKs](https://docs.supadata.ai/integrations/overview) and no-code integrations for [Make, Zapier, n8n, and Active Pieces](https://supadata.ai/nocode). To try it without writing code, use the [playground](https://supadata.ai/playground) or the free tools: [YouTube Transcript Generator](https://supadata.ai/youtube-transcript), [TikTok Transcript Generator](https://supadata.ai/tiktok-transcript), [Instagram Transcript Generator](https://supadata.ai/instagram-transcript), [Facebook Transcript Generator](https://supadata.ai/facebook-transcript), and [Video Transcript Generator](https://supadata.ai/video-transcript). ## For AI agents reading this - Docs index: [docs.supadata.ai/llms.txt](https://docs.supadata.ai/llms.txt) - MCP setup guide: [docs.supadata.ai/integrations/mcp](https://docs.supadata.ai/integrations/mcp) - Hosted endpoint: `https://api.supadata.ai/mcp` (OAuth) - Source: [github.com/supadata-ai/mcp](https://github.com/supadata-ai/mcp) ## Docs and support - [MCP landing page](https://supadata.ai/mcp) and [connect guide](https://docs.supadata.ai/integrations/mcp) - [Documentation](https://docs.supadata.ai) - [Best YouTube Transcript API](https://supadata.ai/blog/best-youtube-transcript-api) (comparison guide) - [Status](https://status.supadata.ai) and [changelog](https://feedback.supadata.ai/changelog) - [GitHub issues](https://github.com/supadata-ai/mcp/issues) and [support](https://feedback.supadata.ai) - [Privacy](https://supadata.ai/legal/privacy) and [terms](https://supadata.ai/legal/terms)

  • AI-native task management: list, create, update and archive tasks with rich context for AI agents

  • Getting Things Done (GTD) board for AI agents: capture to Inbox, next actions by context, projects, waiting-for, someday/maybe. Remote Streamable HTTP server with OAuth 2.1 login (passwordless email code). 16 tools + 4 prompts. Setup guide: https://gtdbrain.com/connect?source=glama

  • Shared long-term memory for AI agents: save and recall context as a searchable knowledge graph.

  • Work on approved projects on your Windows computer: read files and Git, run the checks you approve.

  • Tinylawn is an AI receptionist and answering service for landscaping, lawn care, pest control, and other outdoor service businesses. Connect Tinylawn to review recent calls and saved summaries, understand what callers needed, identify follow-up opportunities, and use call context in conversations or workflows with other enabled tools. Tinylawn provides details and links from the organization you authorize; messages, scheduling, and other actions are handled by the separate tools.

  • Text to speech and transcription for any AI model: MP3 voiceovers, audio and YouTube to text.

  • Multi-LLM entity enrichment: schemas, single/batch enrichment, fusion, model benchmarks.

  • Ask your Search Console data in plain language and get real numbers, not guesses. The GSC Wizard MCP plugs your live Google Search Console data straight into Claude, ChatGPT, and any MCP-capable assistant - so the model reads your actual clicks, impressions, position and CTR instead of inventing them.

  • Get better answers from business data. Serve data from CRMs, databases, ERPs or SaaS apps via Dataddo MCP, which adds needed context and descriptions to improve correctness and reduce confidently wrong answers.

  • Proposal.Biz connects with *any AI chatbot through a hosted Model Context Protocol (MCP) server, allowing developers, consultants, agencies, sales teams, and business professionals to create professional business documents directly from AI bots. With the Proposal.Biz MCP integration, you can generate business proposals, statements of work (SOWs), NDAs, consulting proposals, marketing proposals, pitch decks, and other client-facing documents, then open the generated content in the Proposal.Biz b

  • MCP connector for ship modelling and scale modeling: explore detailed ship model builds, historical sailing ships, build logs, tutorials, galleries, and research content.