"Automated WeChat public account posting tools" matching MCP servers:

Enables discovery of a company's public feature board (Canny, Featurebase, Frill, UserVoice, Productboard) from its domain and retrieval of its most-voted requests with votes, status, comments, and the integrations customers ask for. Supports monitoring runs that surface only new requests, status changes, and vote jumps since a prior run using a saved state key.

MCP server that exposes project status tools (plan, milestones, RAID items, blockers) allowing AI assistants to retrieve and analyze project information via natural language.

Turns your AI host into a product videographer — scripted screen recordings of your own web app with a gliding cursor, camera zooms, highlight callouts, captions, and branded transitions, plus marketing-grade screenshots. Automatic dark-frame cleanup and MP4/GIF export. Free, MIT, 100% local — no account, no API keys.

Provides access to Upvote.club public API via stdio, enabling task creation, status checking, platform listing, and API reference queries.

Enables AI assistants to search new software launches, read product pages, find alternatives, and follow daily rankings from inside a chat using public read-only data.

Enables MCP clients to query the IndeCX public API for survey data, including actions, questionnaires, answers, invites, non-respondents, categories, blocklists, and branches.

Wildberries product analytics by article number with no account or API token: price, discount, rating, reviews, stock, delivery time, price history and competitor comparison. Optional seller tools via the official WB API (sales, orders, stocks, replies to reviews and questions).

Enables customer-success teams and AI hosts to inspect account evidence, assess onboarding readiness, assemble unsent bilingual follow-up drafts, and prepare traceable technical handoffs through scoped MCP tools. It preserves source references and distinguishes recorded failures, missing evidence, and possible explanations for human review.

MCP server for reading public Featurebase feedback boards, enabling agents to query user feedback, posts, comments, and statistics.

Connects AI tools to the Dovetail API, enabling them to interact with Dovetail features.

Collect and analyze user feedback from any app via a single API endpoint, with MCP tools for listing, searching, and stats.

Enables AI assistants to search Sunex's lens and imager catalog using natural language queries. It provides tools for finding compatible lenses, sensor specifications, and product details through a public Model Context Protocol server.

Provides free, zero-marginal-cost MCP tools for structured small business teardown, competitor analysis, review intelligence, and market opportunity scanning, returning research methodology for AI models to execute.

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

Enables external agents to inspect and interact with a local single-project workbench via MCP, providing read-only tools for state, audit, resume, readiness, comparison, impact preview, and repair candidates, while proposals are saved for manual confirmation in the workbench.

A demo MCP server exposing an in-memory todo list via tools (add_task, list_tasks, complete_task), a resource, and a prompt, over both stdio and HTTP transports.

Public MCP server for agent-created, human-friendly, short-lived surveys. Enables agents to ask structured questions and retrieve answers.

Enables read-only Jira Data Center insights by default, with opt-in audited write tools, sprint and release health summaries, and structured issue search via MCP.

Enables AI agents to query Mixpanel event data, funnel conversion rates, and retention cohorts via MCP tools or natural language.

MCP server for noise-reduced X (Twitter) search planning and Feedback-to-Fix engineering handoffs. Enables AI agents to generate structured search plans, filter signals, and build handoff packages via MCP tools.

Connects an AI assistant to a dealer account so it can build and link a shop website that shows live vehicle stock and takes enquiries and test-drive bookings with no database to run. It also lets the assistant read and change listings, prices, test drives, reviews and leads in plain language, with read-only access by default and every change written to an audit log.

Integrates AI assistants with product management tools like Linear and Slack, providing specialized agents for discovery, strategy, prioritization, roadmap planning, and metrics definition via the Model Context Protocol.

Enables coding agents to access structured product context (decisions, goals, evidence) from meetings and tools, ensuring they build from actual product decisions.

Provides MCP tools for AI agents to create and read decision decks, propose cards and build plans, and retrieve finished tasks, enabling local decision review workflows with portable task handoffs.

Enables agents to discover and validate SaaS opportunities mined from real user complaints across eight public sources, scoring ideas for commercial intent. Also allows fetching detailed dossiers on specific gaps with source complaints, MVP scope, pricing, competitors, and risks.

Enables consumers, developers, and innovators to browse and filter a catalog of credit, wealth, insurance, and treasury product types, enroll in products, build and publish apps, and create, test, and publish new products through role-scoped tools.

MCP server for ListenME — product research task management via Boxverse AI. Provides 21 tools for managing research tasks, reviewing user feedback, and generating insights.

It exposes a public, authenticated, allowlisted MCP surface for AgentSam Brand and Campaign capabilities, enabling compatible hosts to retrieve brand context, inspect assets, draft and evaluate brand/campaign artifacts, rank concepts, plan, and save authorized records while avoiding private operator control-plane access.

Enables autonomous agents to turn high-level project goals into structured user stories, verifiable Gherkin acceptance criteria, edge cases, and OpenAPI-compatible API contract skeletons through MCP tools.

A local bridge to a hosted feature-request board that lets agents list, inspect, and rank requests and their comments, view board statistics, review competitor claims, draft implementation specs, and move requests between statuses. Read-only by default, with a single status-update tool that can also push a request into the public changelog.