Deep Anime Ai Mcp Server

Created By
rocnubie15 days ago
Overview

Deep Anime AI MCP Server

Deep Anime: Character Art, Portraits, and Scene Design

Node smithery License: MIT MCP Zero Config

A Model Context Protocol server that exposes the canonical Deep Anime AI knowledge surface — image generation workflows and styles, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://deepanime.org

🎨 About Deep Anime AI

Deep Anime (deepanime.org) is an AI image generation platform built specifically for anime-style artwork. It lets users create polished character art, portraits, and scene compositions by typing a text prompt, converting a photograph, or remixing an existing design. Rather than offering a generic image generator with an anime filter bolted on, the site provides a focused suite of tools designed around the anime aesthetic — covering everything from initial concept to final touch-ups within a single integrated workspace. Both casual creators experimenting with character ideas and more serious illustrators looking for fast iteration cycles can access the platform through tiered subscription plans.

Key Features

  • Text-to-Image (Prompt to Character Art): Describe a scene or character in plain text and the platform renders it as anime-style art, with pre-built prompt templates available in a gallery for inspiration.
  • Photo to Anime: Upload a photograph and convert it into stylized anime artwork, with attention to preserving facial details and likeness during the transformation.
  • Character Art Generator: Build original character designs from scratch, controlling style, pose, and visual identity without needing source photography.
  • Anime Image Editor: Adjust composition, color grading, and fine details on generated images directly in the platform, removing the need to export to a separate editor for basic refinements.
  • Character Face Swap: Swap or transplant character faces across different images while maintaining consistent visual style.
  • Character Consistency Across Angles: Remix workflows allow users to iterate on the same character — testing different outfits, poses, or angles — while preserving the core character identity across variations.

Use Cases

  • Portrait creation and stylization: Turning personal photos or reference images into anime-style profile pictures or character portraits.
  • Character design and development: Building out original characters for manga, webcomics, visual novels, or game concepts through iterative generation.
  • Scene and concept art: Composing multi-element scenes with specific backgrounds, lighting moods, and character placements for storytelling or world-building projects.
  • Outfit and pose iteration: Testing visual variations on an established character design — changing costumes, expressions, or viewpoints — without losing character consistency.
  • Content creation for social media: Producing anime-style illustrated content for profile images, fan art, or creative posts at a faster pace than hand-drawing.

Who Is It For

Deep Anime is aimed at two overlapping groups. The first is casual creators — fans, hobbyists, and social media users — who want to generate anime-style images of themselves, original characters, or fictional scenes without prior illustration skills or software knowledge. The second group is more production-focused: indie game developers, comic creators, visual novel writers, and digital illustrators who need a quick and consistent way to prototype character designs or generate reference art. The platform's pricing (with a Lite tier and a Pro tier) reflects this range, making entry-level access affordable while offering higher generation volumes and additional features to users with more demanding workflows.

Tools

list_styles

Return the canonical list of image-generation styles or presets the site exposes. (Deep Anime AI)

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for Deep Anime AI.

Input: no parameters. Returns: text/markdown.

Return the canonical list of official links for Deep Anime AI (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://deepanime/styles — Supported image-generation styles and presets.
  • site://deepanime/pricing — Canonical pricing entry point.
  • site://deepanime/faq — Short FAQ generated from public site metadata.
  • site://deepanime/links — Canonical URLs to share with users.

Prompts

tell_me_about_deepanime

Summarize what the site is, who it's for, and how it works. — Deep Anime AI

try_image_style_deepanime

Recommend a starting image-generation style for a stated goal. — Deep Anime AI

Installation

Install via Smithery

npx -y @smithery/cli install deepanime-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

git clone https://github.com/rocnubie/deepanime-mcp.git
cd deepanime-mcp
pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{
  "mcpServers": {
    "deepanime-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/deepanime-mcp/src/index.mjs"
      ]
    }
  }
}

Debug with MCP Inspector

npx @modelcontextprotocol/inspector node src/index.mjs

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

Server Config

{
  "mcpServers": {
    "deepanime-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/deepanime-mcp/src/index.mjs"
      ]
    }
  }
}
Project Info
Created At
15 days ago
Updated At
15 days ago
Author Name
rocnubie
Star
-
Language
-
License
-
Category
Tags

Recommend Servers

View All
GovQL
@Alex Stout

# govql-mcp-server An MCP (Model Context Protocol) server for [GovQL](https://govql.us) — gives AI clients like Claude Desktop, Claude Code, and Cursor direct access to the US Congressional GraphQL API at [api.govql.us/graphql](https://api.govql.us/graphql) without bespoke HTTP wiring. For the design rationale (why FastMCP-Python, the passthrough+curated philosophy, roadmap through v0.4), see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md). ## What you can do with it Ask an agent questions like: - *"How did Vermont's two senators vote on the most recent nomination?"* - *"Which legislators in the 118th Congress switched parties during their service?"* - *"Compare Senator Sanders' voting record to Senator Murkowski's on cloture votes in the most recent Congress."* The agent picks the right tool, writes the GraphQL query against the live schema, and parses the response — no manual API wrangling. ## Install The server runs as a per-client subprocess over stdio. Pick your client: ### Claude Desktop Edit `claude_desktop_config.json` (Settings → Developer → Edit Config): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` Restart Claude Desktop. The `govql` tools appear in the tools panel. ### Claude Code Add to `.mcp.json` in your project (or `~/.mcp.json` for global): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` ### Cursor Settings → MCP → Add Server. Use the same `command` / `args` as above. ### Other clients Any MCP-compatible client that supports stdio servers will work. The command is `uvx govql-mcp-server` with no required arguments. ## Tools | Tool | Purpose | |---|---| | `execute_graphql` | Run any GraphQL query against the GovQL endpoint. Returns the result plus an `last_ingest` timestamp so the agent can reason about data freshness. | | `list_types` | Returns the names and kinds of every type in the GovQL schema. Optional `kind` filter (`"OBJECT"`, `"INPUT_OBJECT"`, `"ENUM"`, etc.) to narrow further. Start here when you don't know what's queryable. | | `describe_type` | Returns one type's full details — fields, arg signatures, input fields, enum values. Call after `list_types` to learn the shape of a specific type before writing a query. | ## Configuration All env vars are optional — the package is zero-config for end users. | Env var | Default | Purpose | |---|---|---| | `GOVQL_ENDPOINT` | `https://api.govql.us/graphql` | Endpoint to query. Override to point at a local dev stack. | | `GOVQL_TIMEOUT_MS` | `30000` | Per-request HTTP timeout. | | `LOG_LEVEL` | `INFO` | Logging level. Logs go to stderr only (stdout is reserved for the MCP transport). | ## Limits (enforced by the upstream API) - Max query depth: 10 - Max query complexity: ~10 billion points (`first: N` multiplies child cost by N — keep page sizes reasonable on deeply nested queries) - Rate limit: 100 requests / 60 s per source IP A depth or complexity violation surfaces as a GraphQL `errors` entry in the tool response so the agent can adjust and retry. ## Data freshness Every `execute_graphql` response includes a `last_ingest` ISO timestamp. Vote data refreshes hourly; legislator data refreshes daily. ## Status Version 0.1.0 ships three foundational tools: a GraphQL passthrough (`execute_graphql`) and two narrow schema-discovery tools (`list_types`, `describe_type`). Curated higher-level tools (`find_legislator`, `get_voting_record`, `compare_voters`, etc.) are planned for subsequent releases — see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md) for the roadmap. ## Links - [GovQL project site](https://govql.us) - [GraphQL API](https://api.govql.us/graphql) - [Source / issues](https://github.com/govql/govql)

8 hours ago