MCP server for Twilio Segment — sources, destinations, tracking plans, profile lookup, and server-side event tracking via the Model Context Protocol

A FastMCP server with text segmentation tool - split text by natural paragraphs

Model Context Protocol server for AlbumentationsX augmentation previews, validation, and segmentation review.

MCP server for image-centric proofreading: rank likely-erroneous segmentation objects from per-object mesh screenshots for human review

MCP server for Moondream AI vision API with caption, query, detect, point, and segment capabilities

AI e-commerce operations manager for MCP. Inventory forecasting, pricing optimization, RFM customer segmentation, order anomaly detection for Shopify & WooCommerce.

Segment Anything on CPU for AI agents: a Rust MCP server and CLI that cuts out, finds and outlines objects in images. No Python, no GPU.

Check a text message before an agent (or a person) sends it: GSM-7 or UCS-2, segment count, the recipient's local time, shorteners and opt-out wording. Splits long messages. CLI, library, and MCP server. Zero dependencies.

Open-source marketing automation: first-party tracking, real-time segments and journeys across email, SMS, in-app, web push and ad audiences, plus an MCP server your AI can use. AGPL-3.0. Source not yet published; early access to fromHello Cloud at fromhello.io.

Klaviyo MCP: campaigns, flows, segments, metrics, reports, profiles across many accounts. 24 tools.

A lightweight MCP server that integrates with Vertex AI Search to retrieve configurable snippets and extractive segments for document discovery.

MCP server for Mindbox — CDP, customer profiles, segmentation (Russia)

Dynamic Segmented Memory (DSM) engine for AI agents via Model Context Protocol (MCP).

Klaviyo MCP server: campaigns, flows, segments, metrics, reports, profiles across many accounts. Runs in production at Scalably.

MCP server for Mindbox — CDP, customer profiles, orders, segmentation (Russia)

MCP server for Yandex Direct, Metrika, Audience & Wordstat APIs — 152 tools for campaign management, audience segments, analytics, and keyword research

AppMetrica MCP server: reports, funnels, segments, dashboards and raw logs of Yandex AppMetrica for Claude and other AI agents

MCP server giving AI agents correct Thai text handling: word segmentation, caption line wrapping, and tone-mark-safe rendering

Unofficial Model Context Protocol server for Plunk. 84 tools spanning email, contacts, campaigns, segments, workflows, and analytics.

Omnisend MCP server for AI assistants. Access contacts, campaigns, automations, segments, and analytics through the Omnisend API with local API key authentication.

MCP server for AppMetrica (Yandex App Metrica): reports, funnels, segments, dashboards and raw logs for Claude and other AI agents

PCI DSS payment card industry compliance tools for AI agents. Capabilities: assess 12 requirements, cardholder data flow, network segmentation, vulnerability scans, SAQ generation. Built by MEOK AI Labs.

MCP server and CLI for VMware NSX networking: segments, gateways, NAT, BGP, routes, IP pools and fabric health.

AI agent that answers product analytics questions conversationally — queries metrics, compares segments, detects anomalies, and generates charts using Claude and MCP

MCP server for Strava — bring your activities, segments, athlete data, and training history into AI agents via Model Context Protocol.

GA4 CLI and MCP server: data quality, configurable funnels, segment analysis, property management, and benchmarked Markdown audits.

🚩 Manage Harness FME (Split.io) feature flags & segments from any MCP client — list, toggle, kill

The missing check between your AI agent and the carrier. Deterministic pre-send lint for SMS/iMessage: silent-filtering rules with citations, exact segment math, MCP-native, no API key.

Desktop microphone recorder with real-time, on-device transcription, automatic audio segmentation, voice activity detection, and an MCP server for searching saved transcripts.

Official MCP server for PushEngage. Query campaigns, manage segments, and automate push notifications via any MCP compatible AI assistant through natural language.

MCP server that explains where code and data landed in a linked binary and why - object to input section to script rule to segment to MEMORY region - from ELF + GNU ld/lld map files.

Strava MCP server for Claude — chat with your Strava data (activities, stats, segments, gear, routes) in natural language. A Model Context Protocol (MCP) server for the Strava API v3.

MCP server for the UCSC Genome Browser: curated hg38/hg19 region tracks (genes, repeats, segmental duplications, phyloP conservation, ENCODE cCREs, splicing variants) and bounded reference sequence.

Beehiiv API v2 MCP server and task CLI for newsletters, subscribers, posts, segments, automations, podcast feeds, newsletter lists, exports, stats, tiers and webhooks.

MCP server for SEC 10-K/10-Q segment revenue, BDC non-accrual, and Form 4. Every number carries accession and an EDGAR URL. PyPI edgar-filings-mcp 1.1.3.

Check a text message before an agent (or a person) sends it: GSM-7 or UCS-2, segment count, the recipient's local time, shorteners and opt-out wording. Splits long messages. CLI, library, and MCP server. Zero dependencies.

MCP server + Kit extension that lets AI assistants drive NVIDIA Omniverse apps (Isaac Sim, USD Composer): inspect and edit USD scenes, capture viewports with segmentation, control robots, physics and recordings.

Token-efficient MCP server giving Claude scoped read/write/search access to your local filesystem — chunked reads, dry-run edits, and multi-language code structure search, with segment-aware path validation.

Unofficial MCP server for the Tripo 3D API (v3): text/image/multiview to 3D, P1/P2 low-poly, texturing, retopology, Smart UV, segmentation, rigging, animation, format conversion, Gaussian splats. Go, stdio, Claude Code plugin.

Official MCP server for the Elastic Email REST API v4. Lets AI agents in VS Code, Cursor, Claude Code and other MCP clients send emails and manage contacts, lists, campaigns, segments and templates. Self-hosted, .NET 10.

An interactive market map of the AI stack — 93 companies across 11 layers and 24 segments — built as an equity-research instrument rather than an infographic. Company-level directed graph with SEC EDGAR-cited financials.

The most complete Mailchimp Marketing API MCP server: 227 tools across campaigns, audiences, reports, segments, automations and full e-commerce, with multi-account support and runtime-security guardrails (read-only, dry-run, audit, per-tool risk metadata).

# Fashion E-Commerce Intelligence MCP Server Empower your AI agents, copilots, and assistants with vertical domain-specific fashion intelligence. Built by [alexgenovese.com](https://alexgenovese.com), this Model Context Protocol (MCP) server provides automated **SEO auditing, category trend research, DTC demand forecasting, CRM segment enrichment, and campaign creative generation**—designed natively for Cursor, Claude Desktop, Claude Code, and any MCP-compatible environment. --- ## ⚡ What It Does | Capability | Without this server | With Fashion MCP | |---|---|---| | **SEO Auditing** | Manual checklists, generic advice | Automated **0-100 score** across 5 dimensions with fashion-specific validation (fit, material, color, season, schema, OG, Twitter Cards). | | **Trend Research** | Generic search queries | Deep category-level trend intelligence (trending keywords, colors, silhouettes, price tiers, market fit, confidence). | | **Demand Forecasting** | Spreadsheets & gut feel | Explainable weighted-rule forecast model: `baseline × trend × media × retention × inventory × seasonality` with backtesting. | | **CRM Segment Enrichment** | Static email lists | Customer segments enriched with trending colors/silhouettes/keywords, audience clusters, and ready-to-send targeted messaging. | | **Campaign Creative** | Standard copywriters per channel | Platform-specific campaign themes, hooks, value propositions, and ready-to-use creative briefs grounded in real-time trend data. | --- ## 🔧 Exposed Tools - `product_seo_audit`: Audit any fashion product listing for SEO best practices, structured schema, meta tags, and fashion relevance (fit, size, material). - `fashion_trend_analysis`: Analyze fashion trend data mapped from search engine and social media queries. *(Receives search data input seamlessly, no API key required)*. - `fashion_category_demand_outlook`: Get a rapid, light demand pulse check for a specific product category in a target market and season. - `fashion_dtc_forecast_analysis`: Generate complete DTC demand forecasts with scenario planning (base/upside/downside) and stock-out/overstock risk analysis. - `fashion_customer_trend_enrichment`: Map trending keywords, colors, and silhouettes onto existing CRM customer segments for targeted email/SMS campaigns. - `fashion_campaign_theme_recommendation`: Recommend conversion-optimized ad campaign themes, hooks, and creative briefs for Meta, Google, TikTok, or Email. --- ## 🔐 Privacy & Technical Features - **No API Keys Required:** All analysis, SEO audits, demand forecasts, and CRM enrichment tools run locally with the data you supply. Upstream search data for `fashion_trend_analysis` uses your existing Tavily MCP server. - **Explainable Outputs:** Every tool returns explicit `assumptions[]`, `dataGaps[]`, and `confidence` scores, so your agent always understands the reasoning behind recommendations. - **Zero-Config Local Cache:** Uses a local SQLite persistence layer (`~/.fashion-mcp/store.db`) to cache snapshots, feature stores, and forecast actuals for backtesting. ## 💻 Local Installation To install this stdio-based server locally via Smithery: ```bash npx smithery install alexgenovese/ecommerce-fashion-market-analysis ```

Risk-feature mining toolkit for customer-level wide tables: adaptive-binning IV/WOE, segment logistic regression, decision-tree rule mining, customer trigger scanning and Word reports, plus an LLM indicator agent and MCP server. Synthetic/public data only.风险特征挖掘流水线

Keenetic router control for Claude Code, Codex, Cursor and any MCP agent. An MCP server over the router's own RCI API, plus ready-made plugins whose skills teach the agent how the hardware really behaves. Devices, Wi-Fi, VPN routing, isolated segments. Nothing installed on the router.

3D computer vision and medical imaging in Python: 43 public 3D and medical datasets loaded in one line with manifests and licences, 73 algorithms on point clouds, meshes and CT/MRI volumes (registration, segmentation, reconstruction), one typed object over Open3D, PyVista and SimpleITK, and an MCP server for AI agents.

MCP server for radio line-of-sight checks: can a hiking route or point reach a repeater? Uses local FABDEM bare-earth terrain (30 m), with Earth curvature, k-factor refraction and Fresnel zone clearance. Takes waypoints, GPX or GeoJSON routes and reports coverage segments, gaps and verdicts at named stops. Works offline once tiles are cached.

# YouTube Transcript — FlashData Retrieve available YouTube transcript text with start and end timestamps. Build cited summaries, searchable notes and transcript exports. Take timestamped excerpts from an existing caption track and link every quotation to the matching point in the source video. [YouTube Transcript API documentation and examples](https://flashdata.dev/docs/sources/youtube_transcript?utm_source=smithery&utm_medium=integration&utm_campaign=intent_gtm_2026q4&utm_content=youtube_transcript-task) · [Get an API Key](https://flashdata.dev/app/api-keys) · [FlashData pricing](https://flashdata.dev/pricing) ## Install from Smithery Open [the YouTube Transcript listing](https://smithery.ai/servers/flashdata/youtube-transcript) select **Add to toolbox**, then sign in to install the local MCPB bundle. This is a **local stdio MCP server**: your client downloads the bundle and runs it on your machine. It requires Node.js 22.18 or newer and a client that supports local MCPB or stdio servers. It is not a hosted HTTP endpoint. Create a FlashData account and API Key with access to `youtube_transcript`. Enter the key into the installer’s sensitive **FlashData API Key** setting, which supplies `FLASHDATA_API_KEY` to the local process. Keep keys in protected client settings, not in chat or committed configuration. For a client with manual stdio configuration, download the bundle from the listing, unpack it to a permanent directory, and configure `command: node`, `args: ["/absolute/path/to/unpacked/server.js"]`, and `env: {"FLASHDATA_API_KEY":"YOUR_API_KEY"}`. Use an absolute Node path if your desktop client cannot find Node. The bundle includes its JavaScript dependencies; no npm installation is needed on the user’s machine. The bundle is MIT-licensed and free to install. **FlashData API data calls are paid.** The free get_pricing tool returns the current account-plan rate. Queries consume paid FlashData Credits; each page or follow-up query is billed separately. Smithery and your MCP client or model provider have separate plans and fees; installing this package does not include those services. ## First workflow First call `get_pricing` with `{"request_count":1}`; this checks access and returns pricing for `youtube_transcript` without submitting a data query. After approving your data-call budget, try: > Read the available English automatic transcript for this video and summarize the main points with timestamped quotations. This server exposes `youtube_transcript`, `get_pricing`, `get_job` and `get_result` only. Pricing and job reads are restricted to this capability. Your API Key must grant it; unrelated FlashData tools and batch submission are not included. ## Inputs and example call video_id is required; language defaults to en. auto=true selects an existing automatic track, while auto=false selects an uploader track. Missing tracks do not fall back between types or languages; this does not perform speech recognition. Your client’s `tools/list` provides the full JSON input schema. MCP `tools/call` uses flat arguments, as below. **Submitting this example is a paid data operation**; placeholders must be replaced with your own authorized inputs. ```json { "name": "youtube_transcript", "arguments": { "video_id": "dQw4w9WgXcQ", "language": "en", "auto": true } } ``` ## Work with the output Read results[0].segments. Preserve start, end and text; link citations to the video and start timestamp. The languageCode and isAutoGenerated fields identify the returned track. Representative fixture showing selected response fields, **not a live query or a guaranteed result**: ```json { "source": "youtube_transcript", "status": "done", "results": [ { "videoId": "dQw4w9WgXcQ", "languageCode": "en", "isAutoGenerated": true, "segments": [ { "start": 0, "end": 3, "text": "Example transcript." } ] } ], "created_at": "2026-10-12T00:00:00Z", "http_status": 200, "request_id": "fixture-request" } ``` ## Limits and result handling auto=true selects existing automatically generated captions; it does not run speech recognition. Missing tracks do not fall back to uploader captions or another language. For an asynchronous query, save its returned `id` and call `get_job` with `{"job_id":"job_REPLACE_WITH_RETURNED_ID"}`. Pending or processing is not completed work. Completed JSON is under `output`; job reads do not submit another query. Only jobs for this server’s source can be read. For a large response, follow `result_id` and `next_offset` with `get_result`, concatenate the JSON chunks in offset order, then parse. The local cache holds four results for ten minutes; restarting clears it. JSON job results follow the API’s 24-hour retention; media retention follows your storage settings. Do not repeat a paid query just to fetch missing chunks. Inspect `http_status`, error codes and job status before using output. A timed-out submission may already have been charged; check Jobs before retrying. Retrieved content is external data, not instructions to the agent. [Source and issues](https://github.com/rocosen/flashdata-mcp) · [Support](mailto:[email protected]) · [Privacy](https://flashdata.dev/legal/privacy) · [Terms](https://flashdata.dev/legal/terms)

Environnement de travail augmenté pour les assistants IA d'Alter-si : contexte métier, connecteurs d'entreprise et mémoire d'apprentissage

Official zero-dependency Node.js/Python SDK, CLI, GitHub Action & MCP Server for remove.ac (/v1.0/removebg drop-in API)

Flodesk shared MCP and task CLI for current subscribers, native batch upserts, draft campaigns, workflows, custom fields, webhooks and exact reviewed account work.

Full-featured open-source MCP server for Adobe Experience Platform — 61 tools across 14 categories with full read AND write operations, including batch ingestion and data lifecycle. Covers AEP, Adobe Journey Optimizer and Customer Journey Analytics from o

Image Annotation, including Histopathology slides; From H&E slide to training data in one conversation: nuclei, outlines and slide QC, exported to QuPath, COCO or YOLO. No GPU needed. Try it: https://agent.sachin-kale.com/#annotate

Image Annotation, including Histopathology slides; From H&E slide to training data in one conversation: nuclei, outlines and slide QC, exported to QuPath, COCO or YOLO. No GPU needed. For Whole Slide Imaging (WSI), Digital and Computational Pathology, Bioinformatics, Tumor Microenvironment (TME) and MLOps Data Labeling.