"Buffer.com social media scheduling MCP server" matching MCP servers:

Enables AI assistants to inspect, triage, and safely retry media-processing jobs through read/write tools, runbook search, and media probing, with OAuth scopes, rate limiting, idempotency, PII redaction, and human approval before changes.

Provides constraint satisfaction and optimization capabilities to LLMs and AI agents for scheduling, resource allocation, routing, budget optimization, and configuration problems using Google OR-Tools CP-SAT solver.

A resume MCP server that enables AI agents to search work history by keyword or meaning, retrieve detailed company info, and send scheduling emails, turning a static resume into interactive tools.

Enables AI agents to semantically search, ask questions about, and analyze videos, with persistent memory and social media import capabilities.

Provides specialized search capabilities across e-commerce platforms, scientific publications, code repositories, social media, and general web with advanced filtering, including product comparison, research aggregation, and developer tool discovery.

Enables AI and LLM systems to interact with the Buttondown newsletter service, supporting email drafting, scheduling, analytics retrieval, and list management through a Model Context Protocol interface.

An MCP server for Plex Media Server that enables natural language interaction with your media library, including search, browse, and chat features via an optional web app.

Connects AI clients to MindsDB via the MySQL protocol to execute SQL queries, manage databases, and perform semantic searches within knowledge bases. It enables automated workflows through job scheduling and provides seamless integration with external data sources.

Enables MCP clients to audit AI search visibility, generate intent-aligned social content, and assess Agentic Commerce Readiness with remediation files.

A Model Context Protocol server that provides real-time hot trending topics from major Chinese social platforms and news sites.

An MCP server implementation that enables calling iFlytek workflows through the Model Context Protocol, allowing for intelligent workflow scheduling with sequential, parallel, loop, and nested execution modes.

Serverless document and media processing with AI chat. Upload documents, images, video, and audio — extract text with OCR or transcription — query using Amazon Bedrock.

Exposes a private social memory archive to AI assistants via MCP, enabling read-only queries about the user's posts, people, and preferences with tools like search, whoami, and timeline.

Enables authorized AI clients to search locally stored WeChat conversations, media, and attachments, retrieve original-message context, and cite evidence through a local stdio MCP interface.

An MCP server that enables interaction with OnSched's consumer-facing appointment scheduling API through natural language, allowing users to manage bookings, appointments, and scheduling operations.

An MCP server that acts as a personalized interview prep coach, tracking DSA problems, scheduling spaced-repetition revisions, and providing RAG-based concept explanations grounded in your own notes.

Enables federated multi-source research by fanning out queries across web, community, and social sources, deduplicating and interleaving results, and storing a persistent corpus for cross-checking.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

Guaardvark turns your own GPU into a full media studio for any MCP client: generate images, video, music and voice, run a five-role Film Crew, upscale to 8K, and query your indexed documents and code, with nothing leaving your machine. Every tool runs behind a default-deny policy, and every render queues locally and is polled by batch id, so an agent can direct hours of production without a cloud

Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.

Enables AI assistants to search and read a private, local archive of your own Telegram chats, groups and media, so they can answer questions about past conversations. It keeps access read-only toward Telegram, treats message text as untrusted, and lets you choose which chats AI apps may see.

Provides read-only tools to search, browse, and retrieve lessons, lesson-plan seeds, books, age-leveled booklets, chapter audio, and public media URLs, along with deterministic recommendations scored by age band and learning style. Designed for Cursor and Grok Bot, it stores no learner data and returns public links rather than proxying file bytes.

Local-first, read-only MCP server for searching and retrieving cited evidence from archived Telegram chats, including transcripts and media metadata.

Gives any MCP client 27 tools for turning scattered feeds, forums, and media into a persistent, searchable evidence corpus, so an agent can search and import evidence, verify claims with independent-source counting and citation checks, and run multi-round research that produces cited, revisable reports. It also supports adaptive retrieval widening, tiered evidence where only author-written sections count as sources, and honest degradation when no LLM key is available.

TypeScript AI SDK with a built-in MCP client: 58+ MCP servers over 4 transports (stdio, HTTP, SSE, WebSocket), 24+ LLM providers behind one interface, streaming, tool calling, RAG, voice (TTS/STT/realtime), and task scheduling.

Enables AI agents to run 700+ backend actions across data, auth and RBAC, payments and wallets, CRM, hosting, RAG, bots, scheduling, and automation through a single execute tool, remotely or via a stdio bridge.

Enables AI assistants to interact with Strapi CMS instances through REST API operations. Supports content management, media uploads, schema introspection, and multiple server configurations with JWT authentication.

Enables AI agents to read the local, already-logged-in WeChat account's chat history: fetch recent messages per contact for reply suggestions, bulk-export all conversations into a local SQLite index for full-text and semantic search, and export media or Moments timelines as offline HTML. Everything runs locally and read-only on macOS, exposing 15 MCP tools plus a matching CLI.

Enables AI agents to run SearXNG-powered metasearch across multiple engines and categories, with optional vector-based semantic re-ranking of results and Tavily-compatible responses. It also converts many document and media formats—including PDF, Office files, Outlook messages, and audio or YouTube recordings—into text.

Exposes a remote Streamable HTTP MCP endpoint that lets an AI client save, search, and retrieve structured memories, archived conversations, social-account notes, and knowledge documents. Access is scoped by per-client API keys with configurable read/write permission levels, collections, and operations.