"MCP Servers for Podcast Creation and Content Management" matching MCP servers:

MCP server for AI-driven document creation, enabling generation of PowerPoint decks with consistent design themes and auto-generated images via ComfyUI.

Enables AI agents to discover long-tail podcasts through randomized probe queries, trend lookups, and RSS feed peeks, providing cadence, episode length, and feed details without requiring API keys.

Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Search and discover YouTube channels via natural language, track them, and summarize videos without transcripts using Gemini API.

Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

Enables interaction with Prismic through tools for reading documents, managing media assets, and performing content migrations or updates. Supports the Prismic Content, Asset, Migration, and Custom Types APIs with secure write operations and multi-transport support.

Multi-platform content distribution — draft posts, repurpose content, generate carousels, schedule, analyze performance, create threads. 7 MCP tools.

Enables users to look up a Douyin creator by name, public ID, or profile URL and receive the latest video link, like/comment/favorite/share counts, a full timestamped transcript with an AI-reviewed correction and change log, and a content overview. Collection, media download, and local speech transcription are orchestrated as stdio MCP tools so Codex, WorkBuddy, and other compatible clients can run creator research and scheduled checks without extra API keys.

Enables local discovery of research topics, interviews users to uncover their unique perspective, and turns insights into content ideas and short-form Reel scripts.

MCP server for publishing posts and retrieving metrics on social platforms like Telegram, with planned support for YouTube and Instagram.

Exposes employee leave-management operations (add employees, check balance, apply/cancel leave, view history) as MCP tools for AI clients like Claude Desktop to call directly.

Enables log analysis for Tenable Patch Management (SaaS and on-prem) by parsing, de-duplicating, and decoding server/client logs into structured verdicts, ranked issues, and known-issue fixes.

Connects AI assistants to your n8n instance to manage workflows, executions, credentials, and user settings through 31 specialized tools. It enables users to perform n8n operations like workflow creation, activation, and execution history retrieval via natural language.

Analyzes YouTube videos and X (Twitter) feeds to extract transcripts, generate takeaways, TLDRs, social hooks, and comic-style infographics, and syncs results to GitHub, all callable as MCP tools.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

Enables AI clients to browse instruments, items, dimensions, expert assignments, and calculate Content Validity Index (CVI) via a standard MCP interface.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Enables AI models to access IBM FileNet Content Manager capabilities including document management, property extraction, legal holds, and AI-powered document insight through standardized MCP interfaces.

Enables AI models to interact with IBM FileNet Content Manager for document management, folder operations, metadata handling, search, and content extraction through a standardized interface.

Enables managing employee leave records through natural language, including adding employees, listing employees, adding/deleting leave entries, and viewing leave history.

Enables managing employee leave requests (apply, view, list leaves) through Claude desktop using natural language.

Enables detection of AI-generated content from ChatGPT, GPT-4, and Gemini models through the BACH AI Content Detector API.

Enables MCP-compatible clients to access reusable AI content-generation tools for creating blogs, social posts, SEO content, research summaries, and more through the FastAPI backend.

Enables podcast producers and agents to manage multitrack projects, run per-track transcription, perform transcript-driven edits, process audio via FFmpeg, and inspect a read-only DAW timeline over MCP.

Enables natural language leave management, allowing users to check leave balances, apply for leave, and retrieve leave history via MCP tools.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.