content-repurposing-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_repurpose_mapA | Given a source content type (long_video, podcast_episode, blog_or_essay, single_short_video), returns every format it can become and exactly how to adapt it. Omit source for all maps. |
| get_platform_specsA | Platform specs for adapting content: aspect ratio, ideal length, caption style, hashtag norms, hook rule, cadence note. Platforms: tiktok, reels, shorts, reel_carousel, x_thread, linkedin, newsletter. Omit for all. |
| adapt_for_platformA | Given a target platform, returns the adaptation rules to reshape a piece of content for it (aspect, length, hook approach, caption style, hashtags, what NOT to do). Platforms: tiktok, reels, shorts, reel_carousel, x_thread, linkedin, newsletter. |
| extract_atomic_contentA | The 6 atomic content types you can pull from one long asset (pull quotes, clips, stats/receipts, steps/lists, story beats, questions) and what each becomes. Use to break one asset into many posts. |
| get_repurpose_workflowB | The 'film once, cut many' batch workflow: capture one strong asset, extract atomic pieces, adapt each per platform, schedule across the week. Returns the step-by-step. |
| get_full_packA | The complete repurposing library in one payload: repurpose maps, platform specs, atomic types. For full agent context. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool has a distinct purpose: adapting for a platform, extracting atomic content, getting full context, platform specs, repurpose maps, and workflows. However, `get_full_pack` aggregates outputs of other getters, causing minor potential confusion.
All tools follow a `verb_noun` pattern with snake_case. Most use `get_`, but `adapt_for_platform` and `extract_atomic_content` use different verbs, which is acceptable. Naming is clear and predictable.
With 6 tools, the server is well-scoped for content repurposing guidance. Each tool covers an essential aspect without redundancy or bloat.
The tool set covers the full lifecycle: breaking down content (extract_atomic_content), platform adaptation (adapt_for_platform, get_platform_specs), repurpose mapping (get_repurpose_map), and workflow (get_repurpose_workflow). No obvious gaps.